Готові списки джерел за темами / Complication prediction

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Добірка наукової літератури з теми "Complication prediction"

Автор: Grafiati

Опубліковано: 7 червня 2025

Оновлено: 2 серпня 2025

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Статті в журналах з теми "Complication prediction"

Woodfield, John C., Peter M. Sagar, Dinesh K. Thekkinkattil, Praveen Gogu, Lindsay D. Plank, and Dermot Burke. "Accuracy of the Surgeons’ Clinical Prediction of Postoperative Major Complications Using a Visual Analog Scale." Medical Decision Making 37, no. 1 (2016): 101–12. http://dx.doi.org/10.1177/0272989x16651875.

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Background. Although the risk factors that contribute to postoperative complications are well recognized, prediction in the context of a particular patient is more difficult. We were interested in using a visual analog scale (VAS) to capture surgeons’ prediction of the risk of a major complication and to examine whether this could be improved. Methods. The study was performed in 3 stages. In phase I, the surgeon assessed the risk of a major complication on a 100-mm VAS immediately before and after surgery. A quality control questionnaire was designed to check if the VAS was being scored as a l

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Peixoto, Hugo, Lara Silva, Soraia Pereira, Tiago Jesus, Vitor Neves Lopes, and António Carlos Abelha. "Death and Morbidity Prediction Using Data Mining in Perforated Peptic Ulcers." International Journal of Reliable and Quality E-Healthcare 9, no. 1 (2020): 37–49. http://dx.doi.org/10.4018/ijrqeh.2020010104.

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Peptic ulcers are not the most common complication in gastrointestinal mucosa, but these defects stand out as being the complication with the highest mortality rate. Several scoring systems based on clinical and biochemical parameters, such as the Boey and PULP scoring system have been developed to predict the probability of mortality. In this study, a data mining process is performed in the medical data available, in order to evaluate how the scoring systems perform when trying to predict mortality and patients' state complication. Furthermore, the presented paper studies the two scoring syst

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Zuo, Ming, Wei Zhang, Qi Xu, and Dehua Chen. "Deep Personal Multitask Prediction of Diabetes Complication with Attentive Interactions Predicting Diabetes Complications by Multitask-Learning." Journal of Healthcare Engineering 2022 (April 20, 2022): 1–7. http://dx.doi.org/10.1155/2022/5129125.

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Objective. Diabetic complications have brought a tremendous burden for diabetic patients, but the problem of predicting diabetic complications is still unresolved. Our aim is to explore the relationship between hemoglobin A1C (HbA1c), insulin (INS), and glucose (GLU) and diabetic complications in combination with individual factors and to effectively predict multiple complications of diabetes. Methods. This was a real-world study. Data were collected from 40,913 participants with an average age of 48 years from the Department of Endocrinology of Ruijin Hospital in Shanghai. We proposed deep pe

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Devana, Sai K., Akash A. Shah, Changhee Lee, et al. "Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Primary Anatomic Total Shoulder Replacements." Journal of Shoulder and Elbow Arthroplasty 6 (January 2022): 247154922210754. http://dx.doi.org/10.1177/24715492221075444.

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Background The demand and incidence of anatomic total shoulder arthroplasty (aTSA) procedures is projected to increase substantially over the next decade. There is a paucity of accurate risk prediction models which would be of great utility in minimizing morbidity and costs associated with major post-operative complications. Machine learning is a powerful predictive modeling tool and has become increasingly popular, especially in orthopedics. We aimed to build a ML model for prediction of major complications and readmission following primary aTSA. Methods A large California administrative data

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Schallmoser, Simon, Thomas Zueger, Mathias Kraus, Maytal Saar-Tsechansky, Christoph Stettler, and Stefan Feuerriegel. "Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study." Journal of Medical Internet Research 25 (February 27, 2023): e42181. http://dx.doi.org/10.2196/42181.

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Background Micro- and macrovascular complications are a major burden for individuals with diabetes and can already arise in a prediabetic state. To allocate effective treatments and to possibly prevent these complications, identification of those at risk is essential. Objective This study aimed to build machine learning (ML) models that predict the risk of developing a micro- or macrovascular complication in individuals with prediabetes or diabetes. Methods In this study, we used electronic health records from Israel that contain information about demographics, biomarkers, medications, and dis

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Hong, Qing-Qi, Su Yan, Yong-Liang Zhao, et al. "Machine learning identifies the risk of complications after laparoscopic radical gastrectomy for gastric cancer." World Journal of Gastroenterology 30, no. 1 (2024): 79–90. http://dx.doi.org/10.3748/wjg.v30.i1.79.

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BACKGROUND Laparoscopic radical gastrectomy is widely used, and perioperative complications have become a highly concerned issue. AIM To develop a predictive model for complications in laparoscopic radical gastrectomy for gastric cancer to better predict the likelihood of complications in gastric cancer patients within 30 days after surgery, guide perioperative treatment strategies for gastric cancer patients, and prevent serious complications. METHODS In total, 998 patients who underwent laparoscopic radical gastrectomy for gastric cancer at 16 Chinese medical centers were included in the tra

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Kim, Jae Weon, Dong-Hoon Suh, and Jae Hoon Kim. "Prediction of major surgical complications by comprehensive geriatric assessment in elderly patients with gynecologic cancers: A prospective cohort study." Journal of Clinical Oncology 30, no. 15_suppl (2012): e15503-e15503. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.e15503.

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e15503 Background: To evaluate the ability of a preoperative comprehensive geriatric assessment (CGA) to predict the risk of postoperative complications in elderly patients who underwent primary surgery for gynecologic cancers. Methods: Fifty-six consecutive patients (24 ovarian, 15 cervical, 6 endometrial, 5 uterine sarcoma, 4 vulvar, and 2 metastatic cancers) older than 70 years scheduled to take surgery electively for gynecologic cancer were preoperatively assessed by CGA. Every category of CGA was evaluated for in-hospital postoperative complications and mortality within 30 days of surgery

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Healthcare Engineering, Journal of. "Retracted: Deep Personal Multitask Prediction of Diabetes Complication with Attentive Interactions Predicting Diabetes Complications by Multitask-Learning." Journal of Healthcare Engineering 2023 (September 20, 2023): 1. http://dx.doi.org/10.1155/2023/9891682.

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Kim, Jae Weon, Dong-Hoon Suh, Mi-Kyung Kim, et al. "Prediction of major surgical complications by comprehensive geriatric assessment in elderly patients with gynecologic cancers: A prospective cohort study." Journal of Clinical Oncology 31, no. 15_suppl (2013): e20530-e20530. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.e20530.

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e20530 Background: To evaluate the ability of a preoperative comprehensive geriatric assessment (CGA) to predict the risk of postoperative complications in elderly patients who underwent primary surgery for gynecologic cancers. Methods: Sixty consecutive patients (26 ovarian, 16 cervical, 7 endometrial, 5 uterine sarcoma, 4 vulvar, and 2 metastatic cancers) older than 70 years scheduled to take surgery electively for gynecologic cancer were preoperatively assessed by CGA. Every category of CGA was evaluated for in-hospital postoperative complications and mortality within 30 days of surgery. Ma

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Coia Jadresic, M., and J. Baker. "DEVELOPMENT OF A PREDICTION MODEL (NZSPINE) FOR SIGNIFICANT ADVERSE OUTCOME AFTER SPINE SURGERY." Orthopaedic Proceedings 105-B, SUPP_3 (2023): 5. http://dx.doi.org/10.1302/1358-992x.2023.3.005.

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Numerous prediction tools are available for estimating postoperative risk following spine surgery. External validation studies have shown mixed results. We present the development, validation, and comparative evaluation of novel tool (NZSpine) for modelling risk of complications within 30 days of spine surgery.Data was gathered retrospectively from medical records of patients who underwent spine surgery at Waikato Hospital between January 2019 and December 2020 (n = 488). Variables were selected a priori based on previous evidence and clinical judgement. Postoperative adverse events were class

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Дисертації з теми "Complication prediction"

SANTORO, FRANCESCO. "Risk Stratification for in-Hospital Complications in Patients with Takotsubo Syndrome: the Geist Score." Doctoral thesis, Università degli Studi di Foggia, 2019. http://hdl.handle.net/11369/382354.

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IMPORTANCE: Takotsubo syndrome (TTS) is an acute reversible heart failure syndrome featured by significant rates of in-hospital complications (IHCs). There is a lack of data for risk stratification during hospitalization. OBJECTIVES: To derive a simple clinical score for risk prediction of IHCs in patients with TTS. DESIGN, SETTING, PARTECIPANTS: 1007 consecutive patients with TTS were enrolled in the GEIST (GErman and Italian STress Cardiomyopathy) registry. The score was developed using a stepwise multivariable regression analysis. The RE-TAKO (Spanish REgistry for TAKOtsubo cardiomyopathy)

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Toofanee, Mohammud Shaad Ally. "An innovative ecosystem based on deep learning : Contributions for the prevention and prediction of diabetes complications." Electronic Thesis or Diss., Limoges, 2023. https://aurore.unilim.fr/theses/nxfile/default/656b0a1f-2ff2-49c5-bb3e-f34704d6f6b0/blobholder:0/2023LIMO0107.pdf.

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En 2021, le diabète touchait environ 537 millions de personnes dans le monde. Ce chiffre devrait grimper à 643 millions d'ici 2030 et 783 millions d'ici 2045. Le diabète est une maladie métabolique persistante qui nécessite des soins et une gestion quotidiens continus. Le fardeau des maladies chroniques pèse lourdement sur les systèmes de santé lorsqu'il touche une partie substantielle de la population. De telles circonstances ont un impact négatif non seulement sur le bien-être général d'une grande partie de la population, mais contribuent également de manière significative aux dépenses de sa

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Affonso, Maria Claudia Nogueira. "Fatores preditores de mortalidade em gêmeos monoamnióticos." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/5/5139/tde-12012016-094618/.

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O presente estudo tem como objetivo descrever a mortalidade fetal e pósnatal em gestações gemelares monocoriônicas monoamnióticas, e analisar fatores preditores do número de crianças vivas no momento da alta hospitalar. Realizado de forma retrospectiva, envolveu pacientes com gestações gemelares monocoriônicas monoamnióticas, com ambos os fetos vivos no primeiro atendimento realizado no Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, no período de 2004 a 2014. Para a análise da proporção de crianças vivas, de acordo com os subgrupos estudados, foi utilizado o teste

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Kingwell, Stephen. "Predicting Complications After Spinal Surgery: Surgeons’ Aided and Unaided Predictions." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41559.

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Despite the emergence of artificial intelligence (AI) and machine learning (ML) in medicine and the resultant interest in predictive analytics in surgery, there remains a paucity of research on the actual impact of prediction models and their effect on surgeons’ risk assessment of post-surgical complications. This research evaluated how spinal surgeons predict post-surgical complications with and without additional information generated by a ML predictive model. The study was conducted in two stages. In the preliminary stage an ML prediction model for post-surgical complications in spine sur

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Liu, Jenny M. Eng Massachusetts Institute of Technology. "An integrative predictive model for hospital acquired complications." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100632.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 45-50). Hospital Acquired Complications (HACs) are a serious problem affecting modern day healthcare institutions. It is estimated that in US hospitals, HACs cause an approximately 10% increase in total inpatient hospital

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Diebold, Kasey Elaine. "Risk factors for wound complications following cesarean delivery." Thesis, University of Iowa, 2014. https://ir.uiowa.edu/etd/1311.

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Background: Cesarean delivery rates have been increasing since 1996, and Cesarean delivery is now the most common major operative procedure performed in the United States. Identifying risk factors for wound complications following Cesarean delivery is necessary to prevent unnecessary maternal morbidity. Methods: A case-control study was carried out and data was collected via a medical record review for patients undergoing a Cesarean delivery at the UIHC between 10/1/2011 and 12/31/2012. Results: Several modifiable risk factors were identified, and models based on patient and surgical factors p

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Nwaukwa, Christian A. "Predictive Relationship between Treatment Adherence Glycated Hemoglobin and Diabetic Complications among Jamaicans." Thesis, Walden University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10977949.

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Patient nonadherence to physicians? prescribed therapeutic regimen is the greatest challenge in the effective treatment of patients with diabetes worldwide. Scientific evidence has revealed that nonadherence to prescribed medication could result in diabetic complications such as cardiovascular disease, retinopathy, nephropathy, and neuropathic diabetic foot ulcers. The purpose of this study was to explore predictive relationships between levels of adherence to antidiabetic medications, patient HbA1c levels, and diabetic complications among Jamaicans, an understudied population. The research

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Nwaukwa, Christian Anaba. "Predictive Relationship between Treatment Adherence, Glycated Hemoglobin and Diabetic Complications Among Jamaicans." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/6076.

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Patient nonadherence to physicians' prescribed therapeutic regimen is the greatest challenge in the effective treatment of patients with diabetes worldwide. Scientific evidence has revealed that nonadherence to prescribed medication could result in diabetic complications such as cardiovascular disease, retinopathy, nephropathy, and neuropathic diabetic foot ulcers. The purpose of this study was to explore predictive relationships between levels of adherence to antidiabetic medications, patient HbA1c levels, and diabetic complications among Jamaicans, an understudied population. The research qu

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Abou, Chakra Claire Nour. "Développement d’outils de prédiction des complications et des récidives de l’infection à Clostridium difficile." Thèse, Université de Sherbrooke, 2017. http://hdl.handle.net/11143/9911.

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Résumé : Depuis 2002, une augmentation des taux d’issues défavorables de l’infection à Clostridium difficile (ICD) a été attribuable à l’émergence de la souche NAP1/BI/R027. Il est indispensable d’identifier les facteurs de risque de développer des complications (ICDc) et des récidives (ICDr), et de pouvoir les prédire lors du diagnostic afin d’optimiser le traitement. Le projet de recherche a comme objectifs: i) l’identification des facteurs de risque pour le développement d’ICDc et ICDr et ii) le développement et la validation d’un outil de prédiction à partir de variables mesurées dans les

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Tran, Diem. "Clinical Prediction Rule for the Development of New Onset Postoperative Atrial Fibrillation After Cardiac Surgery." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/24400.

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This project set out to derive a prediction rule based on preoperative clinical variables to identify patients with high risk of developing atrial fibrillation following cardiac surgery. Methods: Prospectively collected data from a perioperative database was corroborated with chart review to identify eligible patients who had non-emergent surgery in 2010. Details on 28 preoperative variables were collected and significant predictors (p<0.2) were inserted into multivariable logistic regression and recursive partitioning. Results: 305 (30.5%) of 999 patients developed new onset postoperativ

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Книги з теми "Complication prediction"

Nguyen, Phong. Assessment of maximum oxygen consumption (MVo2/ Vo2max) as a predictor of postoperative complications. Laurentian University, 2003.

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Weber, Randal S. A model for predicting transfusion requirements in head and neck surgery. American Laryngological, Rhinological and Otological Society, 1995.

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BEREZhNOY, Aleksandr, Svetlana DUNAEVSKAYa, and Yuriy VINNIK. Prognosis of postoperative course of urolithiasis. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1863093.

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The monograph devoted to the study of urolithiasis consistently highlights the issues of etiology, classification, diagnosis and modern principles of treatment of urolithiasis. The problems of postoperative complications in surgery and urology are considered as a separate issue, data on original methods for predicting the development of hemorrhagic or inflammatory complications in the postoperative period with urolithiasis are presented. Special attention is paid to the issues of nonspecific immune protection, immune status indicators and hemostasis system in the development of complications i

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Bradley, M. J. The determination of serum superoxide free radical generation and its possible role as a predictor of late onset diabetic complications. The Author], 1993.

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United States. President's Cancer Panel. Meeting. President's Cancer Panel Meeting: The human genome project and disease prediction. National Institutes of Health, National Cancer Institute, 1995.

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Chistyakova, Guzel, Lyudmila Ustyantseva, Irina Remizova, Vladislav Ryumin, and Svetlana Bychkova. CHILDREN WITH EXTREMELY LOW BODY WEIGHT: CLINICAL CHARACTERISTICS, FUNCTIONAL STATE OF THE IMMUNE SYSTEM, PATHOGENETIC MECHANISMS OF THE FORMATION OF NEONATAL PATHOLOGY. AUS PUBLISHERS, 2022. http://dx.doi.org/10.26526/monography_62061e70cc4ed1.46611016.

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The purpose of the monograph, which contains a modern view of the problem of adaptation of children with extremely low body weight, is to provide a wide range of doctors with basic information about the clinical picture, functional activity of innate and adaptive immunity, prognostic criteria of postnatal pathology, based on their own research. The specific features of the immunological reactivity of premature infants of various gestational ages who have developed bronchopulmonary dysplasia (BPD) and retinopathy of newborns (RN) from the moment of birth and after

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Spong, Catherine Y. Stillbirth: Prediction, Prevention and Management. Wiley & Sons, Limited, John, 2011.

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Spong, Catherine Y. Stillbirth: Prediction, Prevention and Management. Wiley & Sons, Incorporated, John, 2011.

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Spong, Catherine Y. Stillbirth: Prediction, Prevention and Management. Wiley & Sons, Incorporated, John, 2011.

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Spong, Catherine Y. Stillbirth: Prediction, Prevention and Management. Wiley & Sons, Incorporated, John, 2011.

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Частини книг з теми "Complication prediction"

van Kuijk, Sander M. J., Frank J. W. M. Dankers, Alberto Traverso, and Leonard Wee. "Preparing Data for Predictive Modelling." In Fundamentals of Clinical Data Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99713-1_6.

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AbstractThis is the first chapter of five that cover an introduction to developing and validating models for predicting outcomes for the individual patient. Such prediction models can be used for predicting the occurrence or recurrence of an event, or of the most likely value on a continuous outcome. We will mainly focus on the prediction of binary outcomes, such as the occurrence of a complication, recurrence of disease, the presence of metastases, remission, survival, etc. This chapter deals with the selection of an appropriate study design for a study on prediction, and on methods to manipu

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Lestari, Dian, Fairuz Iqbal Maulana, Satria Fadil Persada, and Puput Dani Prasetyo Adi. "Machine Learning for Perinatal Complication Prediction: A Systematic Review." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5166-6_53.

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Bertrand, Ambre, Carolyna Yamamoto, Giulia Monopoli, et al. "Augmentation of Cardiac Ischemic Geometry for Improving Machine Learning Performance in Arrhythmic Risk Stratification." In Computational Physiology. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53145-3_3.

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AbstractVentricular arrhythmias frequently occur as a complication of myocardial infarction (MI), due to significant changes in the heart’s structure and electrophysiology. If left untreated, these alterations may lead to sudden cardiac death (SCD). It is therefore critical to evaluate risk prediction accurately in post-infarction patients to enable early intervention and improve patient outcomes. This work introduces a novel approach to improve arrhythmia risk assessment in post-infarction patients. We propose a new pipeline to build physiologically realistic image-based models of patient hea

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Zhang, Jingwei, Xiaodong Yang, Yiqiang Chen, and Ruizhe Sun. "C-PPT: A Channel-Wise Prototypical Part Transformer for Interpretable Perioperative Complication Prediction with Blood Pressure." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-78341-8_4.

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Coll, Mar, Elsa Solà, and Pau Sancho-Bru. "Prediction of Complications of Cirrhosis: Molecular Biomarkers." In Complications of Cirrhosis. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13614-1_3.

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Rafiq, Wajahat, Jinesh Surana, J. Thangakumar, and Sambath. "Ensemble-Based Prediction of Myocardial Ischemia Complications." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-68908-6_24.

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Jonker, Soraya M. R., Nayyirih G. Tahzib, and Rudy M. M. A. Nuijts. "Predicting the Unhappy Patient and Patient Expectations." In Management of Complications in Refractive Surgery. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-60561-6_42.

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Aragón-Sánchez, Javier, and Rajgopal Mani. "Predicting Wound Healing in the Diabetic Foot: Measuring Skin Viability." In Management of Diabetic Foot Complications. Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-4525-7_5.

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Hinchliffe, Robert J., and Luke Hopkins. "Predicting Wound Healing in the Diabetic Foot: Measuring Tissue Perfusion." In Management of Diabetic Foot Complications. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-05832-5_5.

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Hosen, Md Imran, Abdullah Nazhat Abdullah, Tarkan Aydin, Md Atiqur Rahman Ahad, and Md Baharul Islam. "Predicting Heatstroke Risk and Preventing Health Complications." In Activity, Behavior, and Healthcare Computing. CRC Press, 2025. https://doi.org/10.1201/9781032648422-16.

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Тези доповідей конференцій з теми "Complication prediction"

Hu, Danqing, Bing Liu, Xiaofeng Zhu, Xudong Lu, and Nan Wu. "KAMLN: A Knowledge-aware Multi-label Network for Lung Cancer Complication Prediction." In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2024. https://doi.org/10.1109/embc53108.2024.10782283.

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Lestari, Dian, Fairuz Iqbal Maulana, Puput Dani Prasetyo Adi, Anita Rahayu, Reny Nadlifatin, and Vandha Pradwiyasma Widartha. "Bibliometric Analysis of Intelligent Techniques for Obstetric Complication Prediction in the Last 20 Years." In 2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA). IEEE, 2024. http://dx.doi.org/10.1109/esmarta62850.2024.10638994.

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Alsalami, Zaid, Bhupchand Kumhar, Neeraj Varshney, M. B. Marasulov, Deeksha Verma, and B. Arun Kumar. "AI-Based Prediction of Respiratory Complications." In 2024 International Conference on Communication, Computing and Energy Efficient Technologies (I3CEET). IEEE, 2024. https://doi.org/10.1109/i3ceet61722.2024.10994161.

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Ranganathan, Chitra Sabapathy, R. Nandhini, K. Nisha, G. Sumathi, G. Sudhakar, and C. Srinivasan. "Random Forests for Predicting Diabetes Progression and Complications." In 2024 3rd International Conference for Advancement in Technology (ICONAT). IEEE, 2024. https://doi.org/10.1109/iconat61936.2024.10774631.

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Baidya, Shriyansh, and Vibhuti Gupta. "Predicting Cardiac Complications of Myocardial Infarction Patients Using Machine Learning." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10826091.

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Alzubaidi, Laith H., N. Jagadeesan, N. Sateesh, Y. M. Mahaboob John, and V. Mangaiyarkarasi. "A Prediction of Complications in Sickle Cell Disease Patients using Regularized Random Forest." In 2024 First International Conference on Software, Systems and Information Technology (SSITCON). IEEE, 2024. https://doi.org/10.1109/ssitcon62437.2024.10797029.

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Prabu, S., Sivakumar K K, Anurag Kumar Tiwari, S. Selvakanmani, Rajesh Tiwari, and Amit Lathigara. "Applying Deep Belief Network for Predicting the Risk of Diabetes Complications." In 2025 4th International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE). IEEE, 2025. https://doi.org/10.1109/icdcece65353.2025.11035676.

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Shi, Zixin, Linjun Huang, and Haolin Wang. "Predicting Complications of Cirrhosis using Synthetic Data Generation Enhanced Dynamic Classifier Selection." In 2024 IEEE International Conference on Medical Artificial Intelligence (MedAI). IEEE, 2024. https://doi.org/10.1109/medai62885.2024.00040.

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ALdausari, Nada, Frans Coenen, Anh Nguyen, and Eduard Shantsila. "Predicting Post Myocardial Infarction Complication: A Study Using Dual-Modality and Imbalanced Flow Cytometry Data." In 16th International Conference on Knowledge Discovery and Information Retrieval. SCITEPRESS - Science and Technology Publications, 2024. http://dx.doi.org/10.5220/0012998300003838.

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Huang, Chih-Hsuan, Li-Chien Tang, Yen-Chun Chen, et al. "Enhancing Diabetes Diagnosis and Complications Prediction with Automated Machine Learning in a Clinical Decision Support System." In 2025 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). IEEE, 2025. https://doi.org/10.1109/icaiic64266.2025.10920865.

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Звіти організацій з теми "Complication prediction"

Feng, Zhichao, Zhimin Yan, and Qianyun Liu. MRI Signs for Prenatal Prediction of Placenta Accreta Spectrum Disorders and Invasiveness in High-risk Pregnant Women: A Systematic Review and Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.11.0003.

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Review question / Objective: This meta-analysis aimed to identify the significant MRI signs for placenta accreta spectrum in high-risk pregnant women and to determine their diagnostic value. Condition being studied: Placenta accreta spectrum (PAS) is a dangerous complication in pregnancies with increasing incidence worldwide, in which the villous tissue adheres or invades the uterine wall. Eligibility criteria: Articles assessing the diagnostic performance of MRI signs for PAS and/or placenta percreta in high-risk pregnant women underwent full-text review. Included studies required confirmatio

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Ferdosian, Hengameh, Hadi Zamanian, Sayed Ali Emami, Elahe Sedighi, Mina Moridi, and Maryam Doustmehraban. Application of artificial intelligence in prediction of cardiovascular complications in patients with diabetes mellitus type 2: A protocol of systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.10.0076.

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Review question / Objective: The aim of this systematic review is to evaluate AI-based models in identifying predictors of cardiovascular events and risk predtion in patients with diabetes mellitus type2. Condition being studied: T2DM patients have an increased risk of macrovascular and microvascular complications, lead to decreased quality of life and mortality. Considering the significance of cardiovascular complications in these patients, prediction of such events would be important. Different traditional statistical methods(such as regression) and new AI-besed algorithms are used to predic

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Huang, Wei, Dahong Yang, Danyang Fan, Chao Hou, and Wanqian Liu. Prognostic value of net water uptake in acute ischemic stroke: a protocol for a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.12.0077.

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Review question / Objective: The purpose of this protocol is to present a transparent and clear methodology for performing a systematic review and meta-analysis of the available literature aimed to answer the following question: among patients with acute ischemic stroke due to large vessel occlusion, is net water uptake (NWU), as measured in CT images, associated with (i) cerebrovascular complications, including malignant cerebral edema, secondary intracerebral hemorrhage, and (ii) post-stroke functional outcome as measured by the modified Rankin Scale. Condition being studied: Currently, the

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Wu, Jyun-Jie. Improving Predictive Efficiency and Literature Quality Assessment for Lung Cancer Complications Post-Proton Therapy Through Large Language Models and Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2024. http://dx.doi.org/10.37766/inplasy2024.8.0103.

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Xie, Hailun, Lishuang Wei, Mingxiang Liu, Guanghui Yuan, Shuangyi Tang, and Jialiang Gan. Preoperative computed tomography-assessed sarcopenia as a predictor of complications and long-term prognosis in patients with colorectal cancer: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2020. http://dx.doi.org/10.37766/inplasy2020.12.0033.

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Gupta, Shikhar, Mehtab Ahmed, Sayema ., Azam Haseen, and Saif Quaiser. Relevance of Preoperative Vessel Mapping and Early Postoperative Ultrasonography in Predicting AV Fistula Failure in Chronic Kidney Disease Patients. Science Repository, 2024. http://dx.doi.org/10.31487/j.rdi.2023.02.02.

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Introduction: The increasing prevalence of chronic kidney disease (CKD), coupled with advancements in the diagnosis and treatment of renal diseases and improvements in life expectancy, has led to a greater number of patients requiring hemodialysis. The preferred method of vascular access for hemodialysis is AV fistula formation; however, it is associated with a high rate of failure. In our prospective study, we focused on 40 CKD patients planned for initiation of maintenance hemodialysis. Methods: We employed preoperative ultrasound mapping to assess cephalic vein diameter, compressibility, an

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Gong, Xuan, Zhou Chen, Kui Yang, et al. Endoscopic Transsphenoidal Surgery for Infra-Diaphragmatic Craniopharyngiomas: Impact of Diaphragm Sellae Competence on Hypothalamic Injury. International Journal of Surgery, 2024. http://dx.doi.org/10.60122/j.ijs.2024.20.03.

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Objective: Investigate the impact of diaphragm sellae competence on surgical outcomes and risk factors for postoperative hypothalamic injury (HI) in patients undergoing endoscopic transsphenoidal surgery (ETS) for infra-diaphragmatic craniopharyngiomas (ICs). Methods: A retrospective analysis of 54 consecutive patients (2016-2023) with ICs treated by ETS was conducted. All tumors originated from the sellar region inferior to the diaphragm sellae and were classified into two subtypes in terms of diaphragm sellae competence: IC with competent diaphragm sellae (IC-CDS) and IC with incompetent dia

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Puthanakit, Thanyawee, Kiat Ruxrungtham, Chitsanu Pancharoen, Jintanat Ananworanich, Torsak Burunupradah, and Arunee Klinklom. Pharmacokinetics of low-dose lopinavir/ritonavir tablet formulation in HIV-1 infected children. Chulalongkorn University, 2010. https://doi.org/10.58837/chula.res.2010.14.

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Methods: This was an open-label, cross-over study of 24 HIV-infected children with HIV RNA < 50 copies/ml comparing PK parameter of standard dose LPV/r and low dose of LPV/r for 4 weeks. LPV dosage was prescribed by body weight band; 25~35 kg: LPV/r 300/75 vs. 200/50 mg, > 35 kg 400/100 vs. 300/75 mg. Glood samples were drawn at 0 (pre-dose), 2,4,6,8, 10 and 12 hours. Plasma concentrations of LPV and RTV were measured by HPLC method. The acceptable C12h is > 1 mg/L. The HIV RNA was measured at week 12 after switch back to standard dose for 4 weeks. Results: Twenty four children were i

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Sowjanya, Dr Kaniti, Dr Bongu Srinivas, and Dr Metta Lakshmana Rao. A STUDY ON FIBROSCAN COMPARED TO AST TO PLATELET RATIO INDEX(APRI) FOR ASSESSMENT OF LIVER FIBROSIS WITH NONALCOHOLIC FATTY LIVER DISEASE(NAFLD). World Wide Journals, 2023. http://dx.doi.org/10.36106/ijar/1606016.

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Background : Nonalcoholic fatty liver disease (NAFLD) is increasingly recognized as a cause of chronic liver disease, and often results in the devastating outcomes of decompensated liver cirrhosis and hepatocellular carcinoma and is an important feature of metabolic syndromes and insulin resistance. The assessment of liver brosis is essential for predicting the prognosis and outcome of all forms of chronic liver disease. A liver biopsy is the gold standard for the assessment of liver brosis, but it has its limitations, which include life-threatening complications. Alternative methods of non-

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