AIMC Topic: Machine Learning

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Detection of preceding sleep apnea using ECG spectrogram during CPAP titration night: A novel machine-learning and bag-of-features framework.

Journal of sleep research
Obstructive sleep apnea (OSA) has a heavy health-related burden on patients and the healthcare system. Continuous positive airway pressure (CPAP) is effective in treating OSA, but adherence to it is often inadequate. A promising solution is to detect...

A review of machine learning applications for the proton MR spectroscopy workflow.

Magnetic resonance in medicine
This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured over...

DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues.

BMC bioinformatics
BACKGROUND: P4 medicine (predict, prevent, personalize, and participate) is a new approach to diagnosing and predicting diseases on a patient-by-patient basis. For the prevention and treatment of diseases, prediction plays a fundamental role. One of ...

Machine learning approaches for data-driven process monitoring of biological wastewater treatment plant: A review of research works on benchmark simulation model No. 1(BSM1).

Environmental monitoring and assessment
In the past decade, machine learning techniques have seen wide industrial applications for design of data-based process monitoring systems with an aim to improve industrial productivity. An efficient process monitoring system for wastewater treatment...

The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review.

Frontiers in public health
BACKGROUND: Artificial intelligence (AI) is a broad outlet of computer science aimed at constructing machines capable of simulating and performing tasks usually done by human beings. The aim of this scoping review is to map existing evidence on the u...

Stenosis Detection and Quantification of Coronary Artery Using Machine Learning and Deep Learning.

Angiology
The aim of this review is to introduce some applications of artificial intelligence (AI) algorithms for the detection and quantification of coronary stenosis using computed tomography angiography (CTA). The realization of automatic/semi-automatic ste...

Reduced Order Machine Learning Models for Accurate Prediction of CO Capture in Physical Solvents.

Environmental science & technology
CO sorption in physical solvents is one of the promising approaches for carbon capture from highly concentrated CO streams at high pressures. Identifying an efficient solvent and evaluating its solubility data at different operating conditions are hi...

The Use of Machine Learning for Image Analysis Artificial Intelligence in Clinical Microbiology.

Journal of clinical microbiology
The growing transition to digital microbiology in clinical laboratories creates the opportunity to interpret images using software. Software analysis tools can be designed to use human-curated knowledge and expert rules, but more novel artificial int...

A reinforcement federated learning based strategy for urinary disease dataset processing.

Computers in biology and medicine
Urinary disease is a complex healthcare issue that continues to grow in prevalence. Urine tests have proven valuable in identifying conditions such as kidney disease, urinary tract infections, and lower abdominal pain. While machine learning has made...

High Throughput Read-Across for Screening a Large Inventory of Related Structures by Balancing Artificial Intelligence/Machine Learning and Human Knowledge.

Chemical research in toxicology
Read-across is an in silico method applied in chemical risk assessment for data-poor chemicals. The read-across outcomes for repeated-dose toxicity end points include the no-observed-adverse-effect level (NOAEL) and estimated uncertainty for a partic...