research Patient Perspectives regarding Artificial Intelligence-Driven Trichoscopy for Alopecia Evaluation
Patients found AI helpful for alopecia diagnosis but want it to support, not replace, doctors.
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research Teledermatology in Alopecia: A Systematic Review
Teledermatology is highly effective for diagnosing and managing hair loss.
research Dermacen Analytica: A Novel Methodology Integrating Multi-Modal Large Language Models with Machine Learning in tele-dermatology
The new AI system improves remote skin condition diagnosis and access to care.
research Diagnosis of childhood and adolescent growth hormone deficiency using transcriptomic data
Childhood growth hormone deficiency can be accurately diagnosed using gene expression data and random forest analysis.
research Dermoscopy in female androgenic alopecia: Method standardization and diagnostic criteria
Trichoscopy can diagnose female hair loss with high accuracy by looking for specific patterns in hair and scalp appearance.
research Can Artificial Intelligence “Hold” a Dermoscope?—The Evaluation of an Artificial Intelligence Chatbot to Translate the Dermoscopic Language
AI chatbots can help teach dermatology but need careful checking for accuracy.
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 Anti-Mullerian Hormone as A new Marker for Diagnosis of Poly Cystic Ovary Syndrome
AMH is a reliable marker for diagnosing PCOS.
research Analysis of trichoscopic images using deep neural networks for the diagnosis and activity assessment of alopecia areata – a retrospective study
AI can accurately diagnose and assess alopecia areata using scalp images.
research Dermatology position paper on the revision of the 1982 ACR criteria for systemic lupus erythematosus
The paper concludes that the 1982 criteria for diagnosing systemic lupus erythematosus need updating to improve accuracy and involve dermatologists in the process.
research Prevalence and accurate diagnosis of polycystic ovary syndrome in adolescents across world regions: a systematic review and meta-analysis
PCOS affects about 6.3% of teens globally, and ongoing checks are advised for those with irregular cycles or high androgen levels.
research How good is artificial intelligence (AI) at solving hairy problems? A review of AI applications in hair restoration and hair disorders
AI is effective in diagnosing and treating hair disorders, including detecting hair loss and scalp conditions with high accuracy, but it should supplement, not replace, doctor-patient interactions.
research A Study on the Development of a Web Platform for Scalp Diagnosis Using EfficientNet
A web platform was created to help diagnose scalp conditions accurately and easily.
research Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach -- A Review
Deep learning effectively diagnoses scalp disorders, but improvements are needed.
research MANAGEMENT OF ENDOCRINE DISEASE Hyperandrogenic states in women: pitfalls in laboratory diagnosis
Diagnosing hyperandrogenism in women is complex and requires accurate testing methods and consideration of SHBG levels.
research Clinical Diagnosis of COVID-19: a Prompt, Feasible, Costless, and Highly Sensitive Diagnostic Tool for COVID-19 Based on a 1,757-Patient Cohort (The AndroCoV Clinical Scoring for COVID-19 Diagnosis).
The AndroCoV Clinical Scoring is an accurate, easy, and free way to diagnose COVID-19 without a lab test.
research Clinical diagnosis of COVID-19: a prompt, feasible, and sensitive diagnostic tool for COVID-19 based on a 1,757-patient cohort (The AndroCoV Clinical Scoring for COVID-19 diagnosis)
The study concludes that the new clinical scoring system is a quick, low-cost, and accurate method for diagnosing COVID-19.
research Clinical diagnosis of COVID-19: a prompt, feasible, and sensitive diagnostic tool for COVID-19 based on a 1,757-patient cohort (The AndroCoV Clinical Scoring for COVID-19 diagnosis).
The AndroCoV Clinical Scoring is a quick, affordable, and accurate method for diagnosing COVID-19.
research Comparative Analysis of Machine Learning Algorithms in Diagnosis of Polycystic Ovarian Syndrome
The Random Forest algorithm was the most accurate at diagnosing Polycystic Ovarian Syndrome.
research A machine learning approach for non-invasive PCOS diagnosis from ultrasound and clinical features
Machine learning can accurately diagnose PCOS non-invasively using clinical and ultrasound features.
research Identification of Potential Biomarkers for Diagnosis of Patients with Methamphetamine Use Disorder
Gene expression in hair follicles can help diagnose methamphetamine use disorder.
research Analyse trichoskopischer Bilder mit tiefen neuronalen Netzen zur Diagnose und Aktivitätsbewertung von Alopecia areata – eine retrospektive Studie
Deep-learning models can effectively diagnose and assess Alopecia areata using scalp images.
research DIAGNOSTIC VALUE OF TRICHOSCOPY IN THE DIFFERENTIAL DIAGNOSIS OF VARIOUS FORMS OF ALOPECIA
Trichoscopy is essential for accurately diagnosing and differentiating types of hair loss.
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 The AndroCoV Clinical Scoring for COVID-19 Diagnosis: A Prompt, Feasible, Costless, and Highly Sensitive Diagnostic Tool for COVID-19 Based on a 1757-Patient Cohort
The AndroCoV Clinical Scoring is a quick, accurate, and free tool for diagnosing COVID-19.
research Prostate specific antigen (PSA) in diagnosis of polycystic ovarian syndrome – a new insight
PSA levels are higher in women with PCOS, but FAI is a more accurate marker for diagnosis.
research Hepatocyte growth factor combined with adenosine deaminase as biomarker for diagnosis of tuberculous pleural effusion
HGF combined with ADA is highly accurate for diagnosing tuberculous pleural effusion, especially in younger females.
research Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods
Machine learning can help find new ways to treat alopecia areata.
research PEDL-XAI: A Hybrid Probabilistic Ensemble Deep Learning Approach for Hair Disorder Diagnosis
The new AI system accurately diagnoses hair disorders and offers personalized treatment recommendations.
research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM
Machine learning and deep learning can effectively diagnose alopecia areata.