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Temporal Variability in Stride Kinematics during the Application of TENS: A Machine Learning Analysis.

Medicine and science in sports and exercise
INTRODUCTION: The purpose of our report was to use a Random Forest classification approach to predict the association between transcutaneous electrical nerve stimulation (TENS) and walking kinematics at the stride level when middle-aged and older adu...

A Deep Learning Framework for Analysis of the Eustachian Tube and the Internal Carotid Artery.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Obtaining automated, objective 3-dimensional (3D) models of the Eustachian tube (ET) and the internal carotid artery (ICA) from computed tomography (CT) scans could provide useful navigational and diagnostic information for ET pathologies ...

Automated Measurement and Three-Dimensional Fitting of Corneal Ulcerations and Erosions via AI-Based Image Analysis.

Current eye research
PURPOSE: Artificial intelligence (AI)-tools hold great potential to compensate for missing resources in health-care systems but often fail to be implemented in clinical routine. Intriguingly, no-code and low-code technologies allow clinicians to deve...

Machine learning-enhanced noninvasive prenatal testing of monogenic disorders.

Prenatal diagnosis
OBJECTIVE: Single-nucleotide variants (SNVs) are of great significance in prenatal diagnosis as they are the leading cause of inherited single-gene disorders (SGDs). Identifying SNVs in a non-invasive prenatal screening (NIPS) scenario is particularl...

Navigating merits and limits on the current perspectives and ethical challenges in the utilization of artificial intelligence in psychiatry - An exploratory mixed methods study.

Asian journal of psychiatry
BACKGROUND: The integration of Artificial Intelligence (AI) in psychiatry presents opportunities for enhancing patient care but raises significant ethical concerns and challenges in clinical application. Addressing these challenges necessitates an in...

Are the criteria for PD-MCI diagnosis comprehensive? A Machine Learning study with modified criteria.

Parkinsonism & related disorders
BACKGROUND: Mild cognitive impairment in Parkinson's disease (PD-MCI) includes deficits in different cognitive domains, and one domain to explore for neurocognitive impairment following the DSM-V is social cognition. However, this domain is not inclu...

Machine learning models for prediction of postoperative venous thromboembolism in gynecological malignant tumor patients.

The journal of obstetrics and gynaecology research
AIM: To identify risk factors that associated with the occurrence of venous thromboembolism (VTE) within 30 days after hysterectomy among gynecological malignant tumor patients, and to explore the value of machine learning (ML) models in VTE occurren...

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.

Diabetes & metabolism journal
BACKGRUOUND: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receive...

The role of artificial intelligence in training ENT residents: a survey on ChatGPT, a new method of investigation.

Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale
OBJECTIVE: The primary focus of this study was to analyze the adoption of ChatGPT among Ear, Nose, and Throat (ENT) trainees, encompassing its role in scientific research and personal study. We examined in which year ENT trainees become involved in c...

Leveraging radiomics and machine learning to differentiate radiation necrosis from recurrence in patients with brain metastases.

Journal of neuro-oncology
OBJECTIVE: Radiation necrosis (RN) can be difficult to radiographically discern from tumor progression after stereotactic radiosurgery (SRS). The objective of this study was to investigate the utility of radiomics and machine learning (ML) to differe...