AIMC Topic: Humans

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Construct prediction models for low muscle mass with metabolic syndrome using machine learning.

PloS one
BACKGROUND: Metabolic syndrome (MetS) and sarcopenia are major global public health problems, and their coexistence significantly increases the risk of death. In recent years, this trend has become increasingly prominent in younger populations, posin...

Predicting mortality dynamics in cancer patients: A machine learning approach to pre-death events.

PloS one
Capturing the dynamic changes in patients' internal states as they approach death due to fatal diseases remains a major challenge in understanding individual pathologies and improving end-of-life care. However, existing methods primarily focus on spe...

Comprehensive analysis of disulfidptosis-related genes in pulmonary hypertension through machine learning and immune infiltration: Spotlight on USP32 and ZNF655 as key regulators.

PloS one
BACKGROUND: Disulfidptosis, a novel cellular death manner, has yet to be fully explored within the context of pulmonary arterial hypertension (PAH). This study aims to identify genes implicated in PAH that are involved in disulfidptosis.

Understanding financial hardship in families of people living with dementia: Protocol for a scoping review to identify subjective self-report measures that evaluate financial hardship.

PloS one
BACKGROUND: Financial hardship (including financial stress, financial strain, asset depletion, and financial toxicity) is a highly relevant construct among the 6.9 million people living with Alzheimer's disease and related dementias (ADRD) in the Uni...

Separation, characterization, AI screening, and bioactivities of marine bioactive peptides: A review.

Food chemistry
Marine bioactive peptides (MBPs) are short-chain amino acid polymers derived from marine sources that possess specific physiological activities. Owing to their unique origins and structural diversity, MBPs have attracted considerable research interes...

YOLOv5-aided paper-based microfluidic intelligent sensing platform for multiplex sweat biomarker analysis.

Biosensors & bioelectronics
Sweat, a biofluid rich in various biomarkers, offers significant potential for non-invasive health monitoring and disease screening. Colorimetric detection is well-suited for multi-analyte quantification and point-of-care testing in sweat analysis, w...

HPDAF: A practical tool for predicting drug-target binding affinity using multimodal features.

European journal of medicinal chemistry
Accurate prediction of drug-target binding affinity is crucial for efficient drug discovery and design, enabling researchers to better understand molecular interactions and accelerate the identification of promising drug candidates. Despite recent ad...

Exploring the survival benefits of surgical treatment for pancreatic adenocarcinoma using the DeepSurv neural network model.

Computer assisted surgery (Abingdon, England)
To develop a DeepSurv model for predicting survival in pancreatic adenocarcinoma patients, evaluating the benefit of surgical versus non-surgical treatment across different stages, including stage IV subcategories. Clinical data were extracted from t...

Advances and Challenges in Machine Learning for RNA-Small Molecule Interaction Modeling: Review.

Journal of chemical theory and computation
RNA plays a pivotal role in biological processes such as gene expression regulation and protein synthesis. Targeting RNA with small molecules offers a novel therapeutic strategy for various diseases by directly modulating these processes. However, th...

Profiling the Chemical Exposomic Landscape of Esophageal Squamous Cell Carcinoma.

Environmental science & technology
While the cancer genome is well-studied, the nongenetic exposome of cancer remains elusive, particularly for regionally prevalent cancers with poor prognosis. Here, by employing a combined knowledge- and data-driven strategy, we profile the chemical ...