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Despite advances in surgical techniques and care, postoperative complications are prevalent and effects up to 15% of the patients who underwent a major surgery. The objective of this study is to develop and validate models for predicting…

The current best practice approach for the retrospective diagnosis of adverse drug events (ADEs) in hospitalized patients relies on a full patient chart review and a formal causality assessment by multiple medical experts. This evaluation…

Background: Major postoperative complications are associated with increased short and long-term mortality, increased healthcare cost, and adverse long-term consequences. The large amount of data contained in the electronic health record…

Human-Computer Interaction · Computer Science 2020-07-28 Meghan Brennan , Sahil Puri , Tezcan Ozrazgat-Baslanti , Rajendra Bhat , Zheng Feng , Petar Momcilovic , Xiaolin Li , Daisy Zhe Wang , Azra Bihorac

Objective: To improve prediction of Chronic Kidney Disease (CKD) progression to End Stage Renal Disease (ESRD) using machine learning (ML) and deep learning (DL) models applied to an integrated clinical and claims dataset of varying…

Quantitative Methods · Quantitative Biology 2025-05-06 Yubo Li , Rema Padman

The accuracy of coronary artery disease (CAD) diagnosis is dependent on a variety of factors, including demographic, symptom, and medical examination, ECG, and echocardiography data, among others. In this context, artificial intelligence…

Artificial Intelligence · Computer Science 2023-08-30 Elham Nasarian , Danial Sharifrazi , Saman Mohsenirad , Kwok Tsui , Roohallah Alizadehsani

We developed deep learning models for predicting Total Knee Replacement (TKR) need within various time horizons in knee osteoarthritis patients, with a novel capability: the models can perform TKR prediction using a single scan, and…

Image and Video Processing · Electrical Eng. & Systems 2025-03-31 Haresh Rengaraj Rajamohan , Richard Kijowski , Kyunghyun Cho , Cem M. Deniz

$\textbf{Objective}$ Develop an automatic diagnostic system which only uses textual admission information from Electronic Health Records (EHRs) and assist clinicians with a timely and statistically proved decision tool. The hope is that the…

Computation and Language · Computer Science 2017-12-08 Christy Li , Dimitris Konomis , Graham Neubig , Pengtao Xie , Carol Cheng , Eric Xing

Heart disease remains the leading cause of death in the United States. Compared with risk assessment guidelines that require manual calculation of scores, machine learning-based prediction for disease outcomes such as mortality can be…

Machine Learning · Computer Science 2018-12-13 Laura A. Barrett , Seyedeh Neelufar Payrovnaziri , Jiang Bian , Zhe He

Hip fractures are a leading cause of death and disability among older adults. Hip fractures are also the most commonly missed diagnosis on pelvic radiographs. Computer-Aided Diagnosis (CAD) algorithms have shown promise for helping…

Chronic kidney disease (CKD) is a significant public health challenge, often progressing to end-stage renal disease (ESRD) if not detected and managed early. Early intervention, warranted by silent disease progression, can significantly…

Machine Learning · Computer Science 2024-11-19 Zachary Dana , Ahmed Ammar Naseer , Botros Toro , Sumanth Swaminathan

Background: Intracranial bleeding (IB) is a life-threatening condition caused by traumatic brain injuries, including epidural, subdural, subarachnoid, and intraparenchymal hemorrhages. Rapid and accurate detection is crucial to prevent…

Chronic kidney disease (CKD) affects millions worldwide and progresses irreversibly through stages culminating in end-stage renal disease (ESRD) and death. Outcome trials in CKD traditionally employ time-to-first-event analyses using the…

Methodology · Statistics 2026-01-27 Jiren Sun , Tuo Wang , Yu Du

Chronic kidney disease (CKD) represents a slowly progressive disorder that can eventually require renal replacement therapy (RRT) including dialysis or renal transplantation. Early identification of patients who will require RRT (as much as…

Machine Learning · Computer Science 2022-09-07 Daniel Lopez-Martinez , Christina Chen , Ming-Jun Chen

In clinical data sets we often find static information (e.g. patient gender, blood type, etc.) combined with sequences of data that are recorded during multiple hospital visits (e.g. medications prescribed, tests performed, etc.). Recurrent…

Machine Learning · Computer Science 2016-11-18 Cristóbal Esteban , Oliver Staeck , Yinchong Yang , Volker Tresp

Time series data are prevalent in electronic health records, mostly in the form of physiological parameters such as vital signs and lab tests. The patterns of these values may be significant indicators of patients' clinical states and there…

Machine Learning · Computer Science 2019-11-18 Kun Zhang , Yuan Xue , Gerardo Flores , Alvin Rajkomar , Claire Cui , Andrew M. Dai

Chronic Kidney Disease (CKD) is a major global health issue which is affecting million people around the world and with increasing rate of mortality. Mitigation of progression of CKD and better patient outcomes requires early detection.…

Artificial Intelligence · Computer Science 2025-04-08 Md. Ehsanul Haque , S. M. Jahidul Islam , Jeba Maliha , Md. Shakhauat Hossan Sumon , Rumana Sharmin , Sakib Rokoni

Background: Hip replacement procedures improve patient lives by relieving pain and restoring mobility. Predicting hip replacement in advance could reduce pain by enabling timely interventions, prioritising individuals for surgery or…

Machine Learning · Computer Science 2024-09-11 Zoe Hancox , Sarah R. Kingsbury , Andrew Clegg , Philip G. Conaghan , Samuel D. Relton

Atrial Fibrillation (AF) is a heart's arrhythmia which, despite being often asymptomatic, represents an important risk factor for stroke, therefore being able to predict AF at the electrocardiogram exam, would be of great impact on actively…

Signal Processing · Electrical Eng. & Systems 2022-02-14 A. Scagnetto , G. Barbati , I. Gandin , C. Cappelletto , G. Baj , A. Cazzaniga , F. Cuturello , A. Ansuini , L. Bortolussi , A. Di Lenarda

Intracerebral hemorrhage (ICH) is a life-risking condition characterized by bleeding within the brain parenchyma. ICU readmission in ICH patients is a critical outcome, reflecting both clinical severity and resource utilization. Accurate…

Machine Learning · Computer Science 2025-01-03 Shuheng Chen , Junyi Fan , Armin Abdollahi , Negin Ashrafi , Kamiar Alaei , Greg Placencia , Maryam Pishgar

Background: Vancomycin, a key antibiotic for severe Gram-positive infections in ICUs, poses a high nephrotoxicity risk. Early prediction of kidney injury in critically ill patients is challenging. This study aimed to develop a machine…

Machine Learning · Computer Science 2025-08-01 Junyi Fan , Li Sun , Shuheng Chen , Yong Si , Minoo Ahmadi , Greg Placencia , Elham Pishgar , Kamiar Alaei , Maryam Pishgar