May 2026 in “International Journal of Scientific Research in Science and Technology” The hybrid ensemble model improves scalp disease detection accuracy and consistency.
3 citations
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August 2024 in “Applied Sciences” A web platform was created to help diagnose scalp conditions accurately and easily.
EfficientNet improves accuracy in diagnosing hair loss stages.
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
June 2026 in “Zenodo (CERN European Organization for Nuclear Research)” ScalpViT accurately diagnoses similar-looking scalp diseases with 94.3% accuracy.
January 2026 in “JDDG Journal der Deutschen Dermatologischen Gesellschaft” Deep-learning models can effectively diagnose and assess Alopecia areata using scalp images.
June 2026 in “Zenodo (CERN European Organization for Nuclear Research)” ScalpViT accurately diagnoses similar scalp diseases with 94.3% accuracy.
June 2026 in “Zenodo (CERN European Organization for Nuclear Research)” ScalpViT accurately diagnoses similar-looking scalp diseases with 94.3% accuracy.
61 citations
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June 2022 in “IEEE Journal of Biomedical and Health Informatics” The new method improves skin cancer detection in imbalanced datasets.
July 2026 in “International Journal of Advanced Research in Science Communication and Technology” BaldGraphFormer accurately predicts early baldness, aiding better hair loss treatment.
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
1 citations
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May 2025 in “Journal of Digital Information Management” VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
1 citations
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August 2023 in “arXiv (Cornell University)” Deep learning effectively diagnoses scalp disorders, but improvements are needed.
1 citations
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January 2023 in “IEEE access” Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
March 2026 in “Aesthetic Plastic Surgery” AI is revolutionizing non-surgical cosmetic procedures by improving personalization, safety, and access.
January 2026 in “ITM Web of Conferences” Better datasets and methods are needed for reliable vitiligo detection using deep learning.
February 2024 in “Frontiers in physics” The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
January 2024 in “International Journal of Advanced Computer Science and Applications” Deep learning and explainable AI are improving scalp disorder diagnosis, but challenges in transparency and data quality remain.
158 citations
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January 2015 in “Artificial Intelligence in Medicine” DrugNet effectively identifies new uses for existing drugs and may save resources in drug development.
April 2018 in “DSpace@MIT (Massachusetts Institute of Technology)” Nephronectin is linked to worse outcomes in breast cancer and helps cancer spread.
32 citations
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March 2018 in “Neoplasia” Nephronectin is linked to worse breast cancer outcomes and helps cancer spread.
April 2023 in “Journal of Investigative Dermatology” The improved EczemaNet more reliably and clearly identifies and assesses the severity of atopic dermatitis from photos.
June 2026 in “Scientific Reports” Nestin-expressing hair follicle cells may be useful for nerve repair and regeneration.
6 citations
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February 2025 in “Scientific Reports” MEGA PROTAC improves prediction and ranking of protein complexes better than existing methods.
March 2025 in “Journal of Burn Care & Research” The hemostatic net improves skin graft success and reduces complications.
1 citations
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August 2012 in “Research in Pharmaceutical Sciences”
July 2020 in “bioRxiv (Cold Spring Harbor Laboratory)” Neutrophil extracellular traps slow down hair follicle healing after injury.
April 2026 in “Zenodo (CERN European Organization for Nuclear Research)” The model improves understanding of androgen interactions by focusing on signal intensity and system capacity.
September 2004 in “Experimental Dermatology” The model effectively studies how sensory nerves interact with skin components, aiding research on wound healing and hair growth.
July 2025 in “Journal of Neonatal Surgery” The Advanced Precipitation U-Net Model improves early hair fall detection with 92% accuracy.