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Development of a machine learning approach for prediction of red blood cell transfusion in patients undergoing Cesarean section at a single institution.

Scientific reports
Despite recent advances in surgical techniques and perinatal management in obstetrics for reducing intraoperative bleeding, blood transfusion may occur during a cesarean section (CS). This study aims to identify machine learning models with an optima...

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data.

JMIR public health and surveillance
BACKGROUND: Multimorbidity is a significant public health concern, characterized by the coexistence and interaction of multiple preexisting medical conditions. This complex condition has been associated with an increased risk of COVID-19. Individuals...

Perceptions of artificial intelligence system's aptitude to judge morality and competence amidst the rise of Chatbots.

Cognitive research: principles and implications
This paper examines how humans judge the capabilities of artificial intelligence (AI) to evaluate human attributes, specifically focusing on two key dimensions of human social evaluation: morality and competence. Furthermore, it investigates the impa...

Automated identification and segmentation of urine spots based on deep-learning.

PeerJ
Micturition serves an essential physiological function that allows the body to eliminate metabolic wastes and maintain water-electrolyte balance. The urine spot assay (VSA), as a simple and economical assay, has been widely used in the study of mictu...

Artificial Intelligence-Driven Prediction Revealed CFTR Associated with Therapy Outcome of Breast Cancer: A Feasibility Study.

Oncology
INTRODUCTION: In silico tools capable of predicting the functional consequences of genomic differences between individuals, many of which are AI-driven, have been the most effective over the past two decades for non-synonymous single nucleotide varia...

Evaluating machine learning algorithms to predict lameness in dairy cattle.

PloS one
Dairy cattle lameness represents one of the common concerns in intensive and commercial dairy farms. Lameness is characterized by gait-related behavioral changes in cows and multiple approaches are being utilized to associate these changes with lamen...

Using machine learning to predict acute myocardial infarction and ischemic heart disease in primary care cardiovascular patients.

PloS one
BACKGROUND: Early recognition, which preferably happens in primary care, is the most important tool to combat cardiovascular disease (CVD). This study aims to predict acute myocardial infarction (AMI) and ischemic heart disease (IHD) using Machine Le...

Protocol of the study for predicting empathy during VR sessions using sensor data and machine learning.

PloS one
Virtual reality (VR) technology is often referred to as the 'ultimate empathy machine' due to its capability to immerse users in alternate perspectives and environments beyond their immediate physical reality. In this study, participants will be imme...

Fully and Weakly Supervised Deep Learning for Meniscal Injury Classification, and Location Based on MRI.

Journal of imaging informatics in medicine
Meniscal injury is a common cause of knee joint pain and a precursor to knee osteoarthritis (KOA). The purpose of this study is to develop an automatic pipeline for meniscal injury classification and localization using fully and weakly supervised net...