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Pioglitazone, Trimipramine, and Dimetindene may be repurposed to treat psoriasis.

Deep learning effectively diagnoses scalp disorders, but improvements are needed.

Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.

AI can improve alopecia areata diagnosis with high accuracy.

AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.

The Random Forest algorithm was the most accurate at diagnosing Polycystic Ovarian Syndrome.

Combining multiple algorithms predicts hair fall more accurately than using single algorithms.

A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.

Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.

The random forest model effectively helps diagnose COVID-19 using key factors like age and symptoms.

A hat with sensors can measure scalp moisture well, helping with hair care.

The FAW-FS algorithm improves depression recognition, and psychological interventions help AGA patients' mental health.

Machine learning can accurately diagnose PCOS non-invasively using clinical and ultrasound features.

AI can effectively predict COVID-19 mortality risk using patient data.

The models can help find better inhibitors for conditions like baldness and prostate disorders.

The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.

AI improves accuracy and consistency in diagnosing male pattern hair loss.

An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.

Machine learning can accurately predict hair loss early, improving treatment options.

Machine learning and single-cell analysis improve understanding and treatment of wound healing.

A new method accurately measures cell changes in breast cancer.

Reviewers suggested the study on finding new drug uses through social media side-effects needs better methods and clearer limitations.

The study improved and was accepted despite initial concerns about data clarity, methodology, and potential overfitting.

Traditional Chinese medicine may help treat ischemic stroke by targeting specific genes and pathways.

The method can effectively extract biomedical information without needing expert annotation, performing better than previous models.

The method accurately detects diabetes with 94% effectiveness, reducing misdiagnosis risk.

Forensic DNA phenotyping faces challenges due to inconsistent terminology, limited genetic understanding, and debates over technology and models.

VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.

WomenCare helps predict PCOD risk in women to encourage early medical consultation.

The method improves hair image segmentation accuracy while reducing annotation costs.