research LEVERAGING MACHINE LEARNING METHODS IN PREDICTING AND ANALYZING THE ASSOCIATION BETWEEN DIETARY INFLAMMATORY INDEX AND ALOPECIA
Inflammatory diets may increase the risk and severity of alopecia areata.
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60-90 / 1000+ resultsresearch Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for nonspecific orbital inflammation
The LTF gene may help predict and manage nonspecific orbital inflammation.
research Innovative approaches to baldness detection and management with artificial intelligence and machine learning
research Treatment options and emotional well-being in patients with rosacea: An unsupervised machine learning analysis of over 200,000 posts
Rosacea patients often discuss treatments and emotional struggles online, highlighting the need for professional support.
research The role of 3Rs in the age of One Health: where we are and where we’re going
Innovative methods are reducing animal testing and improving biomedical research.
research A Hybrid Transfer Learning Approach Using Obesity Data for Predicting Cardiovascular Diseases Incorporating Lifestyle Factors
Adding obesity data to machine learning models improves heart disease prediction accuracy.
research Predicting Physical Appearance from Low Template: State of the Art and Future Perspectives
Machine learning improves DNA predictions for eye and hair color, but challenges remain for skin tone and facial features.
research Quantitative analysis and development of alopecia areata classification frameworks
A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
research Abstracts from the 2024 WDS Forum - virtual option
5-alpha reductase inhibitors and spironolactone don't increase gynecological tumor risk, glucagon-like-peptide-1 receptor agonists may increase alopecia risk, sanitary pads can cause dermatitis, early hidradenitis suppurativa intervention is crucial for Hispanic patients, community education boosts skin cancer awareness, metformin may improve skin cancer survival, LNG-IUDs can increase acne risk, machine learning accurately detects basal cell carcinoma, JAK-inhibitors may raise miscarriage risk, inclusive skincare ads affect those with darker skin, and CCCA in Black women might involve autoimmunity.
research Advancements in Dermatological Imaging Modalities
New imaging technologies improve skin diagnosis but face cost and training challenges.
research Regenerative Strategies for Androgenetic Alopecia: Evidence, Mechanisms, and Translational Pathways
New regenerative treatments show promise in improving hair growth for androgenetic alopecia.
research A State-of-the-Art Overview on (Epi)Genomics and Personalized Skin Rejuvenating Strategies
Personalized skin rejuvenation using genomics shows promise but needs more research.
research Estimating Scalp Moisture in a Hat Using Wearable Sensors
A hat with sensors can measure scalp moisture well, helping with hair care.
research A DEEP LEARNING APPROACH FOR DIAGNOSIS OF COVID-19 INFECTION AND ITS RELATED FACTORS: A POPULATION-BASED STUDY
The random forest model effectively helps diagnose COVID-19 using key factors like age and symptoms.
research A Comprehensive Survey on Vitiligo Detection Using Deep Learning
Better datasets and methods are needed for reliable vitiligo detection using deep learning.
research 706 Predictive modeling of patient response to JAK/STAT inhibitors and dynamic patient-matching
Machine learning can predict how well patients with alopecia areata will respond to certain treatments.
research Bias Assessment and Data Drift Detection in Medical Image Analysis: A Survey
Reliable machine learning in medical imaging needs bias checks and data drift detection for consistent performance.
research Ensemble of pre-learned deep learning model and an optimized LSTM for Alopecia Areata classification
The new model improves Alopecia Areata classification accuracy to 93.1%.
research Uncharted waters
New DNA analysis and machine learning are advancing forensic science, improving accuracy and expanding into non-human applications.
research Artificial intelligence in dermatology: а scoping review
AI in dermatology shows high accuracy in diagnosing skin diseases but needs more research for improvement.
research THE POTENTIAL OF AI TO ENHANCE MEDICAL EDUCATION: OPPORTUNITIES, CHALLENGES, AND ETHICAL CONSIDERATIONS
AI can greatly improve medical education by personalizing learning and enhancing skills, but challenges like cost, training, and ethics need addressing.
research Hair color digitization through imaging and deep inverse graphics
A new method accurately captures and renders hair color for virtual reality and hair dye use.
research Smart Diagnostic System for Health Risk Assessment
WomenCare helps predict PCOD risk in women to encourage early medical consultation.
research OBLICZA WIRTUALNEJ RZECZYWISTOŚCI: WPŁYW NA CHIRURGIĘ ESTETYCZNĄ I PERCEPCJĘ WŁASNEGO WIZERUNKU
Social media and virtual reality increase dissatisfaction with natural appearance, boosting demand for aesthetic surgery.
research Circulating MicroRNA Signatures in Severe Alopecia Areata: Diagnostic Discrimination, Pathway Analysis, and Therapeutic Implications
Distinct miRNA signatures could help diagnose and treat severe Alopecia Areata.
research Deep Insight of Design, Mechanism, and Cancer Theranostic Strategy of Nanozymes
Nanozymes show promise for effective and safe cancer treatment.
research Performance exploration of multi-gene panels of alopecia areata susceptibility and drug-binding targets
Methotrexate, resveratrol, and curcumin may help treat alopecia areata by targeting immune cells.
research Artificial Intelligence in Healthcare – A Review
AI can greatly improve healthcare by enhancing disease prevention, detection, diagnosis, and treatment.
research Identification and single-cell analysis of prognostic genes related to mitochondrial and neutrophil extracellular traps in bladder cancer
Six key genes can predict bladder cancer outcomes and may serve as prognostic biomarkers.
research Application of big data analytics in minoxidil drug development: a data-driven model for predicting efficacy and side effect risks
The model predicts minoxidil's effectiveness and side effects better than traditional methods.