AIMC Topic: Humans

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SCU-Net: A deep learning method for segmentation and quantification of breast arterial calcifications on mammograms.

Medical physics
PURPOSE: Measurements of breast arterial calcifications (BAC) can offer a personalized, non-invasive approach to risk-stratify women for cardiovascular diseases such as heart attack and stroke. We aim to detect and segment breast arterial calcificati...

CYPlebrity: Machine learning models for the prediction of inhibitors of cytochrome P450 enzymes.

Bioorganic & medicinal chemistry
The vast majority of approved drugs are metabolized by the five major cytochrome P450 (CYP) isozymes, 1A2, 2C9, 2C19, 2D6 and 3A4. Inhibition of CYP isozymes can cause drug-drug interactions with severe pharmacological and toxicological consequences....

Hybrid COVID-19 segmentation and recognition framework (HMB-HCF) using deep learning and genetic algorithms.

Artificial intelligence in medicine
COVID-19 (Coronavirus) went through a rapid escalation until it became a pandemic disease. The normal and manual medical infection discovery may take few days and therefore computer science engineers can share in the development of the automatic diag...

Balanced Convolutional Neural Networks for Pneumoconiosis Detection.

International journal of environmental research and public health
Pneumoconiosis remains one of the most common and harmful occupational diseases in China, leading to huge economic losses to society with its high prevalence and costly treatment. Diagnosis of pneumoconiosis still strongly depends on the experience o...

CIDO ontology updates and secondary analysis of host responses to COVID-19 infection based on ImmPort reports and literature.

Journal of biomedical semantics
BACKGROUND: With COVID-19 still in its pandemic stage, extensive research has generated increasing amounts of data and knowledge. As many studies are published within a short span of time, we often lose an integrative and comprehensive picture of hos...

Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality.

Molecular cancer
BACKGROUND: Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a significant effect on cell viability. This concept can be exploited to specifically target tumor cells...

Hybrid Gradient Descent Grey Wolf Optimizer for Optimal Feature Selection.

BioMed research international
Feature selection is the process of decreasing the number of features in a dataset by removing redundant, irrelevant, and randomly class-corrected data features. By applying feature selection on large and highly dimensional datasets, the redundant fe...

The Increasing Centrality of Robotic Technology in the Context of Nursing Care: Bioethical Implications Analyzed through a Scoping Review Approach.

Journal of healthcare engineering
At the dawn of the fourth industrial revolution, the healthcare industry is experiencing a momentous shift in the direction of increasingly pervasive technologization of care. If, up until the 2000s, imagining healthcare provided by robots was a pure...

Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data.

Diabetes & metabolic syndrome
AIMS: This research work presented a comparative study of machine learning (ML), including two objectives: (i) determination of the risk factors of diabetic nephropathy (DN) based on principal component analysis (PCA) via different cutoffs; (ii) pred...

Robot Death and Human Grief in Films: Qualitative Study.

Omega
Extant grief studies examine the way humans mourn the loss of a nonhuman, be it an animal, object, or abstract concept. Yet little is known about grief when it comes to robots. As humans are increasingly brought into contact with more human-like mach...