AIMC Topic: Humans

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Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain.

Scientific reports
This paper presents an analysis of trunk movement in women with postnatal low back pain using machine learning techniques. The study aims to identify the most important features related to low back pain and to develop accurate models for predicting l...

Development of Automated Triggers in Ambulatory Settings in Brazil: Protocol for a Machine Learning-Based Design Thinking Study.

JMIR research protocols
BACKGROUND: The use of technologies has had a significant impact on patient safety and the quality of care and has increased globally. In the literature, it has been reported that people die annually due to adverse events (AEs), and various methods e...

Effectiveness of Artificial Intelligence (AI) in Clinical Decision Support Systems and Care Delivery.

Journal of medical systems
This review aims to assess the effectiveness of AI-driven CDSSs on patient outcomes and clinical practices. A comprehensive search was conducted across PubMed, MEDLINE, and Scopus. Studies published from January 2018 to November 2023 were eligible fo...

Multidisciplinary cancer disease classification using adaptive FL in healthcare industry 5.0.

Scientific reports
Emerging Industry 5.0 designs promote artificial intelligence services and data-driven applications across multiple places with varying ownership that need special data protection and privacy considerations to prevent the disclosure of private inform...

Age prediction from 12-lead electrocardiograms using deep learning: a comparison of four models on a contemporary, freely available dataset.

Physiological measurement
The 12-lead electrocardiogram (ECG) is routine in clinical use and deep learning approaches have been shown to have the identify features not immediately apparent to human interpreters including age and sex. Several models have been published but no ...

A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy.

Physics in medicine and biology
This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LET) of protons in proton-beam therapy based on the planned dose distribution and patien...

Navigating the landscape of enzyme design: from molecular simulations to machine learning.

Chemical Society reviews
Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is c...

Deep learning applied to dose prediction in external radiation therapy: A narrative review.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Over the last decades, the use of artificial intelligence, machine learning and deep learning in medical fields has skyrocketed. Well known for their results in segmentation, motion management and posttreatment outcome tasks, investigations of machin...

Coagulation Risk Predicting in Anticoagulant-Free Continuous Renal Replacement Therapy.

Blood purification
INTRODUCTION: Continuous renal replacement therapy (CRRT) is a prolonged continuous extracorporeal blood purification therapy to replace impaired renal function. Typically, CRRT therapy requires routine anticoagulation, but for patients at risk of bl...

Seismic hazard analysis and financial impact assessment of railway infrastructure in the US West Coast: A machine learning approach.

PloS one
This research examines the seismic hazard impact on railway infrastructure along the U.S. West Coast (Washington, Oregon and California), using machine learning to explore how measures of seismic hazard such as fault density, earthquake frequency, an...