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- Detection of Serum Levels of Interleukins-17, 21, 6 and Tumor Necrosis Factor-α in Patients with Patchy Alopecia Areata and Their Association with Disease Severity
- Scalp Disease Detection Using Deep Learning: A Hybrid Ensemble Approach with EfficientNetB0, DenseNet121 and MobileNetV2
- Hair and Scalp Disease Detection using Machine Learning and Image Processing
- New Frontiers of Non‐Invasive Detection in Scalp and Hair Diseases: A Review of the Application of Novel Detection Techniques
- Hair and Scalp Disease Detection using Machine Learning and Image Processing
- Hair and scalp disease detection using deep learning
- A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
- Multi-Class Support Vector Machine Classification for Detecting Alopecia Areata and Scalp Diseases
- Inorganic Nanozymes: Prospects for Disease Treatments and Detection Applications
- Hair & Scalp Disease Detection Using Machine Learning & Image Processing
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- ‘Long term use of fin/dut may be associated with health risks including fatty liver disease, insulin resistance, type 2 diabetes, dry eye disease and potential kidney disease.’
- Pattern hair loss before the age of 35 is associated with higher chances of prostate cancer, cardiovascular diseases, and metabolic syndrome later in life
- Androgenetic alopecia is a skin disease: DHT-mediated skin disorders
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