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This study developed the CATNIP computational model, which uses biological and chemical information to successfully identify drug repurposing opportunities for various conditions, including Parkinson’s disease and Type 2 Diabetes.

This review discusses the data resources and computational models used in drug repositioning, highlighting their role in discovering unknown drug mechanisms and reports no new empirical results.

This thesis presents a new scientific approach using specific models to gain insights into psoriasis and eczema, highlighting a molecular classifier that improves diagnostic accuracy and predicts therapeutic response for these conditions.

CEC levels may be a useful marker for predicting prostate cancer progression.

This study presents a computational approach, CATNIP, which repurposes drugs using only their biological and chemical information, predicting new uses like adrenergic uptake inhibitors for Parkinson's and vandetanib for Type 2 Diabetes.

This study reviews methods to ensure the reliability of machine learning models in medical imaging, focusing on bias detection, data drift assessment, and accuracy estimation without ground truth labels to enhance integration into clinical settings.

This study found that hair transplant surgeons can use a new model to predict the number and distribution of follicular units in donor scalp areas based on patient hair density.

In this study, Gaussian process regression models combined with Grey Wolf optimization were used to predict and optimize phenolic and flavonoid content extraction from Carthamus caeruleus L. rhizomes, showing high accuracy and helping improve understanding and extraction processes through a new interactive tool.

This review discusses the implications of deterministic chaos in pathology, emphasizing its potential impact on predicting biological behavior of lesions, and reports no new experimental results.

This study aims to develop an automatic machine learning-based method using the VGG-19 model to accurately classify various hair and scalp diseases.

This review discusses the current state of research on genetic markers for predicting human phenotypic traits from DNA samples for forensic purposes and reports no new experimental findings.

This review summarizes the state of organoid technology, highlighting its potential to transform biomedical research and regenerative medicine by providing accurate models for disease study, drug discovery, and potentially developing functional organs for transplantation.

This study found that the ALK5 inhibitor TP0427736 inhibited TGF-β signaling in cell and mouse models, suggesting potential as a new treatment for androgenic alopecia.

In this study, the researchers developed a deep learning framework to pre-emptively screen for adverse drug effects, showing strong predictive performance, including for increased bleeding risks with edoxaban compared to other anticoagulants.

This study identifies novel subpopulations of human epidermal melanocytes and specific transcriptional programs that differ from model organisms, providing insights into melanoma dedifferentiation.

This study found that in women with PCOS, suppressive therapy using spironolactone plus oral contraceptives improved hirsutism more effectively than either treatment alone, with initial scores predicting success.

In this study, the integration of artificial intelligence in medicine was discussed, highlighting its potential to enhance diagnostic processes, optimize therapies, and provide advanced patient monitoring despite challenges like data inconsistency and limited model transparency.

This study discovered that androgenetic alopecia disrupts the scalp microbiome balance across the whole scalp, not just areas with hair loss, and introduced a microbial index for early detection and severity prediction.

This study found that both primary Covid-19 infections and exacerbations of existing health conditions influence mortality, with long-term effects being predictable from GLM models.

This study found that reduced plasma DIAPH1 levels were associated with polycystic ovary syndrome, suggesting DIAPH1 as a potential predictive factor for the condition.

This study found that cell-free RNA, particularly DNAJB9, shows potential as a biomarker for diagnosing and prognosing female androgenetic alopecia using a machine learning model.

This study developed a novel hydrogel combining Chlorella extracellular polysaccharide–selenium nanoparticles (EPS-SeNPs) with biocompatible components, which demonstrated strong antibacterial and anti-inflammatory effects, significantly accelerating wound healing in an infected rat model, and enabling pH-based monitoring of healing.

This study, examining perceptible hair density changes in androgenetic alopecia patients, found that dermatologists could accurately detect hair loss at a lower threshold than previously noted, specifically at a 22.66% relative density difference, challenging assumptions about their predictive accuracy based solely on clinical examination.

In this study, the researchers reviewed psychiatric drugs approved between 2002 and 2022 to analyze trends in drug repurposing, finding an increased application of repurposing methods, especially through fixed-dose combinations, and highlighting technologies like SmartCube® to predict efficacy from animal models.

This editorial discusses the potential progression of voiding symptoms over time in men, focusing on benign prostatic hyperplasia, but reports no new research findings.

In this study, the researchers optimized the extraction conditions for crude polysaccharide from Hibiscus rosa-sinensis leaves, achieving a yield of 9.66% and demonstrated strong antioxidant activities in vitro.

This study developed a deep learning-based method that identified 3,620,516 potential drug-disease associations, suggesting a promising tool for large-scale virtual screening in drug research.

Melanoma risk tools need improvement, a gene mutation causes a hair disorder that might be treated by managing cell stress, a potential therapy for a skin-ear disorder involves blocking cell channels, skin wrinkling may indicate lung aging regardless of smoking, and oxidative stress might contribute to common baldness.

This mouse study found that offspring of parents with uveitis showed increased susceptibility to experimental autoimmune uveitis, potentially due to altered immune and cellular processes.

This study demonstrated that genetic markers can predict human ear morphology with moderate to good accuracy, potentially aiding forensic identification in crime scene investigations where traditional DNA matches are unavailable.