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Applying machine learning approaches for predicting obesity risk using US health administrative claims database.

BMJ open diabetes research & care
INTRODUCTION: Body mass index (BMI) is inadequately recorded in US administrative claims databases. We aimed to validate the sensitivity and positive predictive value (PPV) of BMI-related diagnosis codes using an electronic medical records (EMR) clai...

No-reference stereoscopic image quality assessment based on binocular collaboration.

Neural networks : the official journal of the International Neural Network Society
Stereoscopic images typically consist of left and right views along with depth information. Assessing the quality of stereoscopic/3D images (SIQA) is often more complex than that of 2D images due to scene disparities between the left and right views ...

A comprehensive comparison of machine learning models for ICH prognostication: Retrospective review of 1501 intra-cerebral hemorrhage patients from the Qatar stroke database.

Neurosurgical review
Multiple prognostic scores have been developed to predict morbidity and mortality in patients with spontaneous intracerebral hemorrhage(sICH). Since the advent of machine learning(ML), different ML models have also been developed for sICH prognostica...

3-1-3 Weight averaging technique-based performance evaluation of deep neural networks for Alzheimer's disease detection using structural MRI.

Biomedical physics & engineering express
Alzheimer's disease (AD) is a progressive neurological disorder. It is identified by the gradual shrinkage of the brain and the loss of brain cells. This leads to cognitive decline and impaired social functioning, making it a major contributor to dem...

Machine-Learning Model Identifies Patients With Alpha-1 Antitrypsin Deficiency Using Claims Records.

COPD
Identifying patients with rare diseases like alpha-1 antitrypsin deficiency (AATD) is challenging. Machine-learning models may be trained to identify patients with rare diseases using large-scale, real-world databases, whereas electronic medical reco...

Visual Feature-Guided Diamond Convolutional Network for Finger Vein Recognition.

Sensors (Basel, Switzerland)
Finger vein (FV) biometrics have garnered considerable attention due to their inherent non-contact nature and high security, exhibiting tremendous potential in identity authentication and beyond. Nevertheless, challenges pertaining to the scarcity of...

Predicting extended hospital stay following revision total hip arthroplasty: a machine learning model analysis based on the ACS-NSQIP database.

Archives of orthopaedic and trauma surgery
INTRODUCTION: Prolonged length of stay (LOS) following revision total hip arthroplasty (THA) can lead to increased healthcare costs, higher rates of readmission, and lower patient satisfaction. In this study, we investigated the predictive power of m...

Predicting prolonged length of stay following revision total knee arthroplasty: A national database analysis using machine learning models.

International journal of medical informatics
BACKGROUND: As the number of revision total knee arthroplasty (TKA) continues to rise, close attention has been paid to factors influencing postoperative length of stay (LOS). The aim of this study is to develop generalizable machine learning (ML) al...

Facial Action Unit Representation Based on Self-Supervised Learning With Ensembled Priori Constraints.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Facial action units (AUs) focus on a comprehensive set of atomic facial muscle movements for human expression understanding. Based on supervised learning, discriminative AU representation can be achieved from local patches where the AUs are located. ...

radMLBench: A dataset collection for benchmarking in radiomics.

Computers in biology and medicine
BACKGROUND: New machine learning methods and techniques are frequently introduced in radiomics, but they are often tested on a single dataset, which makes it challenging to assess their true benefit. Currently, there is a lack of a larger, publicly a...