AIMC Topic: Humans

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A data science approach for early-stage prediction of Patient's susceptibility to acute side effects of advanced radiotherapy.

Computers in biology and medicine
The prediction by classification of side effects incidence in a given medical treatment is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective...

Toward autonomous robotic prostate biopsy: a pilot study.

International journal of computer assisted radiology and surgery
PURPOSE: We present the validation of PROST, a robotic device for prostate biopsy. PROST is designed to minimize human error by introducing some autonomy in the execution of the key steps of the procedure, i.e., target selection, image fusion and nee...

Machine learning based disease prediction from genotype data.

Biological chemistry
Using results from genome-wide association studies for understanding complex traits is a current challenge. Here we review how genotype data can be used with different machine learning (ML) methods to predict phenotype occurrence and severity from ge...

Bone mineral density response prediction following osteoporosis treatment using machine learning to aid personalized therapy.

Scientific reports
Osteoporosis is a global health problem for ageing populations. The goals of osteoporosis treatment are to improve bone mineral density (BMD) and prevent fractures. One major obstacle that remains a great challenge to achieve the goals is how to sele...

Identification of care tasks for the use of wearable transfer support robots - an observational study at nursing facilities using robots on a daily basis.

BMC health services research
BACKGROUND: To reduce the physical burden of caregivers, wearable transfer support robots are highly desirable. Although these robots are reportedly effective for specific tasks in experimental environments, there is little information about their ef...

Applications of artificial intelligence and machine learning in orthodontics: a scoping review.

Progress in orthodontics
INTRODUCTION: This scoping review aims to provide an overview of the existing evidence on the use of artificial intelligence (AI) and machine learning (ML) in orthodontics, its translation into clinical practice, and what limitations do exist that ha...

Development and Validation of a Magnetic Resonance Imaging-Based Machine Learning Model for TMJ Pathologies.

BioMed research international
The purpose of this study was to propose a machine learning model and assess its ability to classify TMJ pathologies on magnetic resonance (MR) images. This retrospective cohort study included 214 TMJs from 107 patients with TMJ signs and symptoms. A...

Exploring Feasibility of Multivariate Deep Learning Models in Predicting COVID-19 Epidemic.

Frontiers in public health
Mathematical models are powerful tools to study COVID-19. However, one fundamental challenge in current modeling approaches is the lack of accurate and comprehensive data. Complex epidemiological systems such as COVID-19 are especially challenging t...

Clinical Feature-Based Machine Learning Model for 1-Year Mortality Risk Prediction of ST-Segment Elevation Myocardial Infarction in Patients with Hyperuricemia: A Retrospective Study.

Computational and mathematical methods in medicine
Accurate risk assessment of high-risk patients is essential in clinical practice. However, there is no practical method to predict or monitor the prognosis of patients with ST-segment elevation myocardial infarction (STEMI) complicated by hyperuricem...

Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm.

Computational intelligence and neuroscience
In this paper, a deep confidence neural network algorithm is used to design and deeply analyze the risk warning model for stadium operation. Many factors, such as video shooting angle, background brightness, diversity of features, and the relationshi...