AIMC Topic: Machine Learning

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NeoAI 1.0: Machine learning-based paradigm for prediction of neonatal and infant risk of death.

Computers in biology and medicine
BACKGROUND: The Neonatal mortality rate in the United States is 3.8 deaths per 1000 live births, which is comparably higher than other nations.

Prediction of serious outcomes based on continuous vital sign monitoring of high-risk patients.

Computers in biology and medicine
Continuous monitoring of high-risk patients and early prediction of severe outcomes is crucial to prevent avoidable deaths. Current clinical monitoring is primarily based on intermittent observation of vital signs and the early warning scores (EWS). ...

Artificial intelligence in virtual screening: Models versus experiments.

Drug discovery today
A typical drug discovery project involves identifying active compounds with significant binding potential for selected disease-specific targets. Experimental high-throughput screening (HTS) is a traditional approach to drug discovery, but is expensiv...

Past and future uses of text mining in ecology and evolution.

Proceedings. Biological sciences
Ecology and evolutionary biology, like other scientific fields, are experiencing an exponential growth of academic manuscripts. As domain knowledge accumulates, scientists will need new computational approaches for identifying relevant literature to ...

An Artificial Intelligence-Based Reactive Health Care System for Emotion Detections.

Computational intelligence and neuroscience
In the past few years, remote monitoring technologies have grown increasingly important in the delivery of healthcare. According to healthcare professionals, a variety of factors influence the public perception of connected healthcare systems in a va...

Efficient Liver Segmentation from Computed Tomography Images Using Deep Learning.

Computational intelligence and neuroscience
Segmentation of a liver in computed tomography (CT) images is an important step toward quantitative biomarkers for a computer-aided decision support system and precise medical diagnosis. To overcome the difficulties that come across the liver segment...

Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks.

PloS one
In recent years, drug sensitivity prediction has garnered a great deal of attention due to the growing interest in precision medicine. Several computational methods have been developed for drug sensitivity prediction and the identification of related...

Predictive models for human-AI nexus in group decision making.

Annals of the New York Academy of Sciences
Machine learning (ML) and artificial intelligence (AI) have had a profound impact on our lives. Domains like health and learning are naturally helped by human-AI interactions and decision making. In these areas, as ML algorithms prove their value in ...

Radiomic Analysis: Study Design, Statistical Analysis, and Other Bias Mitigation Strategies.

Radiology
Rapid advances in automated methods for extracting large numbers of quantitative features from medical images have led to tremendous growth of publications reporting on radiomic analyses. Translation of these research studies into clinical practice c...

Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions.

Journal of chemical information and modeling
Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation of protein-ligand interactions, and it is of strong interest to develop scoring functions with machine-learning approaches. In this work, by expanding...