AIMC Topic: Machine Learning

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Assessing the readiness of dental electronic health records for machine learning prediction of procedure outcomes: Insights from the bigmouth repository on composite and amalgam restoration survival rates.

Journal of dentistry
OBJECTIVE: Dental electronic health records (EHRs) often lack comprehensive data for evaluating procedure outcomes. Machine learning (ML) enables predictive modeling but its applicability to dental EHR data remains unclear. This study assessed the re...

A preliminary study on cause‑of‑death discrimination and the pathological stage identification in acute ischemia heart disease (AIHD) based on plasma lipidomic technique and machine learning algorithms.

International journal of legal medicine
The sudden death discrimination of acute ischemia heart disease (AIHD) and the determination of the AIHD pathological stage are the difficulties in forensic medicine. More potential biomarkers with high sensitivity and specificity still need to be id...

A machine-learning-based approach to predict early hallmarks of progressive hearing loss.

Hearing research
Machine learning (ML) techniques are increasingly being used to improve disease diagnosis and treatment. However, the application of these computational approaches to the early diagnosis of age-related hearing loss (ARHL), the most common sensory def...

Advances in disease detection through retinal imaging: A systematic review.

Computers in biology and medicine
Ocular and non-ocular diseases significantly impact millions of people worldwide, leading to vision impairment or blindness if not detected and managed early. Many individuals could be prevented from becoming blind by treating these diseases early on...

Leveraging pulse wave signal properties for coronary artery calcification screening in CKD patients.

Computers in biology and medicine
BACKGROUND AND AIMS: Chronic kidney disease (CKD) patients are particularly susceptible to coronary atherosclerosis, which can be assessed using computed tomography (CT)-based coronary artery calcium (CAC) score. However, such a costly examination mi...

Evaluating the relationship between environmental chemicals and obesity: Evidence from a machine learning perspective.

Ecotoxicology and environmental safety
Environmental chemicals are increasingly recognized as important contributors to obesity, yet the number of studies evaluating this relationship remains insufficient. This study aimed to investigate these associations using interpretable machine lear...

Assessing simulation-based supervised machine learning for demographic parameter inference from genomic data.

Heredity
The ever-increasing availability of high-throughput DNA sequences and the development of numerous computational methods have led to considerable advances in our understanding of the evolutionary and demographic history of populations. Several demogra...

Multimodal Wearable Sensing for Biomechanics and Biomolecules Enabled by the M-MPM/VCFs@Ag Interface with Machine Learning Pipeline.

ACS sensors
The addition sensing device of sweat to wearable biostress sensors would eliminate the need for using multiple gadgets for healthcare analysis. Due to the distinct package fashion of sensor interface for biostress and biomolecule, achieving permeabil...

Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries.

Chemical reviews
The nexus of quantum computing and machine learning─quantum machine learning─offers the potential for significant advancements in chemistry. This Review specifically explores the potential of quantum neural networks on gate-based quantum computers wi...

AVP-HNCL: Innovative Contrastive Learning with a Queue-Based Negative Sampling Strategy for Dual-Phase Antiviral Peptide Prediction.

Journal of chemical information and modeling
Viral infections have long been a core focus in the field of public health. Antiviral peptides (AVPs), due to their unique mechanisms of action and significant inhibitory effects against a wide range of viruses, exhibit tremendous potential in protec...