Search

everythingexperts & clinicslearnfaqsresearchcommunity

for

Search:↓

This study reports that an Explainable AI-based hair health prediction system using a novel hybrid model outperformed traditional machine learning methods, achieving high accuracy in predicting key factors and providing personalized recommendations.

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.

This study found that a deep learning approach successfully predicted three types of hair and scalp diseases with high accuracy, despite challenges in dataset availability and image variety.

This study found that higher Dietary Inflammatory Index scores were significantly associated with an increase in both the occurrence and severity of alopecia areata.

This study presents a new method called scMC that effectively distinguishes biological from technical variation in single-cell genomics datasets, demonstrating its ability to accurately align and detect biological signals across various experiments.

This review highlights that drug repositioning offers a cost-effective alternative to traditional drug discovery, especially for treating orphan and resistant diseases like COVID-19, by repurposing existing drugs such as Hydroxychloroquine and Remdesivir.

This study used light sheet fluorescence microscopy to successfully image and analyze calcium oscillations in the root hairs of Arabidopsis thaliana, finding that these oscillations correlate with the root hair growth rate and that auxin affects these properties.

This review discusses recent progress in PENG-based sensors for non-invasive medical diagnosis and treatment but reports no new experimental results.

This review examines the use of computer vision techniques, specifically deep learning architectures and image processing algorithms, for detecting and assessing skin conditions like vitiligo and dermatitis, and highlights the need for disease-specific datasets to improve automated diagnostic tools in dermatology.

This study found that cultured foreskin is not suitable for studying H2A.J-related tissue changes during radiation-induced dermatitis due to existing high H2A.J expression and cytokine secretion even without irradiation.

This study found that higher adherence to healthy dietary patterns such as DASH, AHEI, and MED significantly reduced all-cause mortality in hypertensive patients, with the DASH diet particularly lowering cardiovascular mortality, highlighting diet's role in hypertension management.

This review discusses the growing role of colorimetric sensors in food safety, highlighting their potential to enhance detection accuracy and manageability, while also noting challenges such as environmental interference and the need for further industrial validation.

This study found that ATR-FTIR spectroscopy combined with machine learning effectively differentiated alopecia areata patients from healthy controls with an AUC of 0.85, and also showed promise in predicting treatment response, particularly through alterations in the Amide I band.

This review examines recent advances in bioelectronic nanogenerators for anti-cancer therapy, highlighting various transducing strategies such as photodynamic therapy and electrical stimulation, while also discussing the potential mechanisms for tissue repair and the challenges that lie ahead.

This study introduces AlopeciaDet, a novel feature fusion technique, using camera images to detect Alopecia Areata with 99.45% accuracy, outperforming existing methods by leveraging CRSHOG and ResNet-50 features.

This review highlights the potential of self-powered nanogenerators in revolutionizing biomedical devices by using biomechanical or environmental energy, focusing on applications like regenerative hair growth, drug release patches, and electronic skin while evaluating challenges such as energy efficiency and biocompatibility.

This review discusses the repurposing of natural products for COVID-19 treatment but reports no new clinical findings, highlighting ongoing research to target host and viral mechanisms.

This review highlights recent advances in personalized transdermal drug delivery systems, noting their potential for improved treatment efficacy and safety, but identifies significant challenges in clinical translation.

In this scoping review, researchers observed that while AI-assisted trichoscopy holds promise for standardized assessments of hair and scalp disorders, its clinical translation is limited by small proprietary datasets, inconsistent validation protocols, and a scarcity of real-world clinical studies.

In this laboratory study, researchers observed that mouse vascular endothelial cells exhibit dynamic changes after exposure to ionizing radiation, including a transient endothelial subpopulation that facilitates vascular-epidermal communication and skin repair, with shifting roles in angiogenesis and immune surveillance over time.

This review discusses recent advances in polydopamine-based biomaterials and their growing potential in personalized medicine, but reports no new experimental results; the authors highlight both opportunities and challenges for future applications.

This study suggests that Enterococcus faecium fermentation broth may have anti-aging effects in mice, mainly through modulating gut microbiota and enhancing immunity, with the key component NlpC/P60 potentially boosting host immune responses and increasing beneficial bacterial populations.

This study found that integrating machine learning enhances the predictive accuracy of forensic DNA phenotyping from low template DNA, achieving high accuracy for traits like eye color, although challenges remain for admixed populations and complex traits.

This study developed a deep-learning model that accurately diagnosed alopecia areata with an accuracy of 88.92% and distinguished its activity levels with an accuracy of 83.33%, highlighting the potential for artificial intelligence in improving the diagnosis and treatment of this autoimmune hair loss condition.

This study introduces a novel computational model using fuzzy logic and multi-criteria decision-making techniques to create a triage system for androgenetic alopecia management, stratifying patients into seven severity levels and aiding in resource allocation and treatment planning.

This study concluded that a hair-nourishing formulation combining virgin coconut oil and 4% chilli oil significantly enhanced hair growth in white rats over a 21-day period, while also exhibiting good physical stability under varying storage conditions.

Fusarium sp. strain K-23 helps Arabidopsis plants grow better in salty soil by promoting root hair growth.

This study explored the diversity of melanocyte stem cell subpopulations in the hair follicles of adult female mice and identified novel groups with distinct immune privilege regulation, suggesting a heterogeneous landscape that future research should consider.