AIMC Topic: Humans

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Cost-effectiveness analysis of artificial intelligence (AI) in earlier detection of liver lesions in cirrhotic patients at risk of hepatocellular carcinoma in Italy.

Journal of medical economics
BACKGROUND: Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third most common cause of cancer-related death. Cirrhosis is a major contributing factor, accounting for over 90% of HCC cases. With the high mortality rate...

Machine learning-guided anti-photoaging peptides from Chinese giant salamander skin: Efficient preparation and mechanistic insights.

Food chemistry
Collagen peptides are ubiquitously applied in food systems for their versatile bioactivities but face constraints from labor-intensive enzymatic screening and zoonotic risks from terrestrial sources. This study developed machine learning (ML) models ...

Epigenetic signatures of accelerated aging and immune dysregulation in youth with social anxiety disorder.

Behavioural brain research
Social anxiety disorder (SAD) is a prevalent psychiatric condition with significant psychological and socioeconomic consequences. While its psychological characteristics are well-documented, the underlying molecular mechanisms remain poorly understoo...

TECM-ChI: A TECM network-based method for chromatin interaction prediction.

Gene
Chromatin interactions refer to regulatory relationships formed between chromatin regions through physical contact or spatial proximity, playing a crucial role in genome function, structure, and the development of diseases. In cancer research, for ex...

The Role of Artificial Intelligence in Anesthesia Monitoring and Surveillance.

Anesthesiology clinics
Artificial intelligence (AI) has the potential to significantly improve monitoring in the operating room, allowing us to detect and predict changes in the patient's physiology sooner and better optimize patient care. Currently, clinically available a...

Advancing rare neurological disorder diagnosis: Addressing challenges with systematic reviews and AI-driven MRI meta-trans learning framework for neurodegenerative disorders.

Ageing research reviews
Neurological Disorders (ND) affect a large portion of the global population, impacting the brain, spinal cord, and nerves. These disorders fall into categories such as NeuroDevelopmental (NDD), NeuroBiological (NBD), and NeuroDegenerative (ND) disord...

Clinical predictors of treatment resistant depression.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Despite advances in the treatment of major depressive disorder (MDD) yet a substantial proportion of patients fail to achieve remission and instead develop treatment-resistant depression (TRD). Identifying robust clinical predictors of response is es...

Fusion of bio-inspired optimization and machine learning for Alzheimer's biomarker analysis.

Computers in biology and medicine
Identification of Alzheimer's Disease (AD), especially in its early phases, presents significant challenges due to the nonexistence of reliable biomarkers and effective treatments. Clinical trials for AD medications also suffer from high failure rate...

EEG quantization and entropy of multi-step transition probabilities for driver drowsiness detection via LSTM.

Computers in biology and medicine
Detecting driver drowsiness through electroencephalogram (EEG) poses challenges due to the complexity and variability of brain activity across different subjects. This study proposes a feature extraction pipeline combined with a Long Short-Term Memor...

Letter to the Editor: Robustness of osteoporosis risk prediction models with enhanced statistical analyses.

Computers in biology and medicine
In response to Oka et al.'s letter, we conducted additional statistical analyses to validate the robustness of our osteoporosis risk prediction model using NHANES 2007-2014 data (n = 7924). We evaluated 10 key predictors through Spearman's rho, Kenda...