2 citations
,
November 2025 in “Cancer Imaging” Ultrasound-based radiomics and radiogenomics can improve ovarian cancer diagnosis and treatment, but need better standardization and AI tools.
Machine learning can accurately predict hair loss early, improving treatment options.
September 2025 in “The Open Dermatology Journal” The AI showed high accuracy in diagnosing skin conditions but needs improvement for immunological and infectious disorders.
February 2026 in “Pharmaceuticals” KRDQN effectively predicts adverse drug reactions with high accuracy and clear explanations.
March 2023 in “Applied and Computational Engineering” Deep learning models can analyze scalp diseases effectively.
4 citations
,
December 2021 in “Electronics” The new method predicts post-hair transplant images more accurately than other methods.
January 2026 in “Microsystems & Nanoengineering” New technologies replicate human skin for testing without animals.
Machine learning improves DNA predictions for eye and hair color, but challenges remain for skin tone and facial features.
106 citations
,
August 2024 in “Annals of Medicine and Surgery” AI in robotic surgery improves precision and safety but faces cost and ethical challenges.
79 citations
,
July 2022 in “Sensors” Machine learning can effectively predict type 2 diabetes risk.
63 citations
,
February 2024 in “BMC Psychology” Emotion recognition tech helps devices understand emotions, but more research is needed for complex situations.
57 citations
,
June 2021 in “Science” Women inventors focus more on women's health, but there are few of them.
25 citations
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March 2021 in “Australasian Journal of Dermatology” Ustekinumab successfully treated a man's resistant skin condition when other treatments failed.
23 citations
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April 2025 in “Journal of Clinical Medicine” AI can greatly improve plastic surgery, but ethical care and human aspects must remain a priority.
16 citations
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July 2023 in “Frontiers in Medicine” Reliable, non-invasive tools are needed for better vitiligo diagnosis.
15 citations
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November 2024 in “Pharmaceutics” Peptide drugs now target hard-to-reach proteins more effectively and specifically.
9 citations
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February 2024 in “Indian Dermatology Online Journal” New imaging technologies improve skin diagnosis but face cost and training challenges.
9 citations
,
August 2023 in “Molecules” Two peptides, RMYYY and VMYMI, may be effective anti-inflammatory drugs.
9 citations
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January 2020 in “IEEE Access” The KEBOT system is a highly accurate AI tool for analyzing hair transplants.
8 citations
,
May 2024 in “Diagnostics” AI chatbots can help teach dermatology but need careful checking for accuracy.
8 citations
,
August 2021 in “Computational and Mathematical Methods in Medicine” Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
5 citations
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January 2025 in “BMC Medical Informatics and Decision Making” Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.
5 citations
,
January 2025 in “Burns & Trauma” Machine learning and single-cell analysis improve understanding and treatment of wound healing.
5 citations
,
September 2023 in “Molecules” These methods help understand cell structures and reactions.
5 citations
,
April 2023 in “Drug Design Development and Therapy” Drug repositioning can save time and money but needs more support.
4 citations
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August 2023 in “Materials” New synthetic polymers help improve skin wound healing and can be enhanced by adding natural materials and medicines.
2 citations
,
November 2025 in “Comprehensive Reviews in Food Science and Food Safety” Combining advanced sensors with portable devices could enhance on-site food safety monitoring.
2 citations
,
June 2025 in “Biomolecules” Microbiome analysis, BEVs, and AI can improve PCOS diagnosis and treatment.
2 citations
,
September 2024 in “Diagnostics” A new method accurately measures cell changes in breast cancer.
2 citations
,
November 2021 in “Frontiers in Medicine” New skin imaging, teledermatology, and AI could become key in future dermatology care.