AI Medical Compendium Topic:
Cohort Studies

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Impact of previous transurethral resection of prostate on robot-assisted radical prostatectomy: a matched cohort analysis.

Journal of robotic surgery
We aimed to compare surgical, oncological, and functional outcomes of robot-assisted radical prostatectomy (RARP) in prostate cancer patients with and without prior history of transurethral resection of the prostate (TURP), using a matched cohort ana...

Postoperative delirium prediction using machine learning models and preoperative electronic health record data.

BMC anesthesiology
BACKGROUND: Accurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) d...

Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study.

European radiology
OBJECTIVES: We aim ed to evaluate a commercial artificial intelligence (AI) solution on a multicenter cohort of chest radiographs and to compare physicians' ability to detect and localize referable thoracic abnormalities with and without AI assistanc...

Cohort profile: Japanese human milk study, a prospective birth cohort: baseline data for lactating women, infants and human milk macronutrients.

BMJ open
PURPOSE: The Japanese Human Milk Study, a longitudinal prospective cohort study, was set up to clarify how maternal health, nutritional status, lifestyle and sociodemographic and economic factors affect breastfeeding practices and human milk composit...

Comparing LASSO and random forest models for predicting neurological dysfunction among fluoroquinolone users.

Pharmacoepidemiology and drug safety
BACKGROUND: Fluoroquinolones are associated with central (CNS) and peripheral (PNS) nervous system symptoms, and predicting the risk of these outcomes may have important clinical implications. Both LASSO and random forest are appealing modeling metho...

Measuring Patient Similarity on Multiple Diseases by Joint Learning via a Convolutional Neural Network.

Sensors (Basel, Switzerland)
Patient similarity research is one of the most fundamental tasks in healthcare, helping to make decisions without incurring additional time and costs in clinical practices. Patient similarity can also apply to various medical fields, such as cohort a...

Machine Learning-Based Prediction of Myocardial Recovery in Patients With Left Ventricular Assist Device Support.

Circulation. Heart failure
BACKGROUND: Prospective studies demonstrate that aggressive pharmacological therapy combined with pump speed optimization may result in myocardial recovery in larger numbers of patients supported with left ventricular assist device (LVAD). This study...

Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns.

Cell reports. Medicine
Trajectories of cognitive decline vary considerably among individuals with mild cognitive impairment (MCI). To address this heterogeneity, subtyping approaches have been developed, with the objective of identifying more homogeneous subgroups. To date...

Prostate Cancer: Early Detection and Assessing Clinical Risk Using Deep Machine Learning of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data.

Frontiers in immunology
Detecting the presence of prostate cancer (PCa) and distinguishing low- or intermediate-risk disease from high-risk disease early, and without the need for potentially unnecessary invasive biopsies remains a significant clinical challenge. The aim of...

Deep learning computer-aided detection system for pneumonia in febrile neutropenia patients: a diagnostic cohort study.

BMC pulmonary medicine
BACKGROUND: Diagnosis of pneumonia is critical in managing patients with febrile neutropenia (FN), however, chest X-ray (CXR) has limited performance in the detection of pneumonia. We aimed to evaluate the performance of a deep learning-based compute...