European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Oct 20, 2024
INTRODUCTION: The importance of patient perspectives is increasingly appreciated in clinical practice and academia with formal engagement processes developing worldwide. Digital surgery encompasses intraoperative patient data (including surgical vide...
AIMS: We aimed to create a predictive model utilizing machine learning (ML) to identify new cases of congestive heart failure (CHF) in individuals with diabetes in primary health care (PHC) through the analysis of diagnostic data.
OBJECTIVE: This study aims to assess the impact of LearnGuide, a specialized ChatGPT tool designed to support self-directed learning among medical students.
OBJECTIVE: There are few studies evaluating the accuracy of commercially available AI-powered digital auscultation platforms in detecting valvular heart disease (VHD). Therefore, the utility of these systems for diagnosing clinically significant VHD ...
AIM: To develop a machine learning-based CT radiomics model to preoperatively diagnose occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC) patients.
INTRODUCTION: Tinnitus, the perception of sound without an external auditory stimulus, affects approximately 10-15% of the population and is often associated with significant comorbidities such as headaches. These conditions can severely impact the q...
BACKGROUND: Mesial temporal sclerosis (MTS) is the most common pathology associated with drug-resistant mesial temporal lobe epilepsy (mTLE) in adults. Most atrophic hippocampi can be identified using MRI based on standard epilepsy protocols; however...
PURPOSE: To build and validate a combined radiomics and machine learning (ML) approach using B-mode US and SWE images to differentiate benign from malignant solid breast lesions (BLs) and compare its performance with that of an expert radiologist.
International journal of medical informatics
Oct 18, 2024
OBJECTIVE: Predicting mortality risk following orthopedic surgery is crucial for informed decision-making and patient care. This study aims to develop and validate a machine learning model for predicting one-year mortality risk after orthopedic hospi...
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