AIMC Topic: Humans

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ML-based prediction to experimental validation: Development of dihydroquinazoline based multi-potent ligands as anti-Alzheimer's agents.

Computers in biology and medicine
Alzheimer's disease (AD) is a multifactorial neurological disorder accounting for the cognitive decline in the patients. The disease is linked to numerous pathological factors including hyperactivation of acetylcholinesterase (AChE) and monoamine oxi...

Deep siamese residual support vector machine with applications to disease prediction.

Computers in biology and medicine
Support Vector Machines (SVMs) excel in classification and regression tasks involving high-dimensional nonlinear data, boasting high accuracy, strong generalization ability, and robust performance. Particularly noteworthy is their outstanding perform...

Exploring the potential associations between single and mixed volatile compounds and preserved ratio impaired spirometry using five different approaches.

Ecotoxicology and environmental safety
BACKGROUND: Although the relationship between environmental pollutants and respiratory health has received widespread attention, no studies have explored the association between volatile organic compounds (VOCs) and preserved ratio impaired spirometr...

A novel integrated modelling framework to uncover spatial and temporal evolutionary patterns and influence mechanisms of land use conflicts.

Journal of environmental management
Rapid and disorderly urban expansion leads to productivity loss, habitat fragmentation, and reduced land marginal returns, hindering sustainable urban development. Scientific identification of land use conflicts (LUCs) and understanding their driving...

[Artificial intelligence under scrutiny: requirements, quality criteria, and testing tools for medical applications].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
The use of artificial intelligence (AI) in medicine has great potential to improve quality and efficiency. At the same time, its use is associated with risks. In order to prevent harm, experts from research and politics are developing requirements, t...

Generative AI in hepatology: Transforming multimodal patient-generated data into actionable insights.

Hepatology communications
Cirrhosis care is inherently complex, marked by a high risk of acute decompensation and significant morbidity and mortality. Traditional episodic care models provide static snapshots of a patient's condition, limiting the ability to address dynamic c...

Nanozyme-Enabled Multimodal Sensing: Visual and Rapid Profiling of Extracellular Vesicles.

Analytical chemistry
CD20, a transmembrane protein on the surface of lymphoma extracellular vesicles (EVs), is highly expressed and serves as an effective marker for monitoring lymphoma subtypes and evaluating the efficacy of antibody therapy. Therefore, there is an urge...

Synergizing Nanosensor-Enhanced Wearable Devices with Machine Learning for Precision Health Management Benefiting Older Adult Populations.

ACS nano
Population aging presents significant health challenges and socioeconomic burdens globally, driving an increased demand for precision health management. In the era of big data, the exponential growth of health information is accelerating advances in ...

Machine Learning-Assisted Iterative Screening for Efficient Detection of Drug Discovery Starting Points.

Journal of medicinal chemistry
High-throughput screening (HTS) remains central to small molecule lead discovery, but increasing assay complexity challenges the screening of large compound libraries. While retrospective studies have assessed active-learning-guided screening, extens...

Evaluating the representational power of pre-trained DNA language models for regulatory genomics.

Genome biology
BACKGROUND: The emergence of genomic language models (gLMs) offers an unsupervised approach to learning a wide diversity of cis-regulatory patterns in the non-coding genome without requiring labels of functional activity generated by wet-lab experime...