Transfer learning with three neural network architectures accurately classifies hair diseases.
June 2001 in “International Journal of Cosmetic Surgery and Aesthetic Dermatology” The Hair Implanter Pen increases speed and is gentle on grafts, with users mastering it after a few tries.
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.
3 citations,
July 2023 in “Nature Communications” The ShorT method can detect and help reduce bias in medical AI by identifying shortcut learning.
3 citations,
October 2022 in “Nano Letters” Machine learning identified promising nanozymes for treating hair loss.
1 citations,
February 2024 in “npj digital medicine” Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
1 citations,
January 2023 in “IEEE access” Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
1 citations,
December 2022 in “Sultan Qaboos University medical journal” The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.
The model accurately classifies hair conditions with 97% accuracy.
October 2023 in “Journal of the Endocrine Society” Machine learning identified three unique subtypes of androgen excess in women with PCOS, each with different metabolic risks.
July 2023 in “Dermatology practical & conceptual” The machine learning model effectively assesses the severity of hair loss and could help dermatologists with treatment decisions.
GoogLeNet is the best model for identifying folliculitis.
May 2023 in “Indian journal of science and technology” The new deep learning system can accurately recognize hair loss conditions with a 95.11% success rate.
March 2023 in “Applied and Computational Engineering” Deep learning models can analyze scalp diseases effectively.
December 2022 in “Research Square (Research Square)” The document concludes that an automatic system using deep learning can help diagnose skin disorders, but challenges and opportunities in this area remain.
June 2022 in “Frontiers in Genetics” Machine learning is effective in predicting gene functions and their relationships with diseases.
January 2021 in “Lecture notes in networks and systems” Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
September 2017 in “Indian Journal of Plastic Surgery” Garg and Garg created an affordable, easy-to-use training program for hair restoration surgery using everyday items, which can teach a technician the basics in 3-4 weeks with two hours of daily practice.
December 2021 in “Acta dermato-venereologica” A deep learning model accurately predicts male hair loss types using scalp images.
November 2021 in “Frontiers in Genetics” The FAW-FS algorithm improves depression recognition, and psychological interventions help AGA patients' mental health.
232 citations,
January 2016 in “BMC Bioinformatics” The method can effectively extract biomedical information without needing expert annotation, performing better than previous models.
20 citations,
September 2020 in “International journal of computer applications” The Random Forest algorithm was the most accurate at diagnosing Polycystic Ovarian Syndrome.
8 citations,
August 2020 in “PLOS Computational Biology” A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.
3 citations,
January 2023 in “European Journal of Information Technologies and Computer Science” The machine learning model accurately detected hair loss and scalp diseases using processed images.
2 citations,
November 2008 Problem-based learning in a biology class improved students' thinking and problem-solving skills.
The system can automatically identify different hair and scalp conditions using machine learning.
April 2023 in “Journal of Investigative Dermatology” The AI model somewhat predicts lymph node status in melanoma patients using skin sample images.
August 2019 in “bioRxiv (Cold Spring Harbor Laboratory)” The model successfully predicted new uses for existing drugs, like using certain hormonal and heart medications for respiratory and Parkinson's diseases, and a cancer drug for diabetes.
December 2022 in “International Journal of Molecular Sciences” Afatinib, neratinib, and zanubrutinib could be effective against KRASG12C-mutant tumors.
3 citations,
May 2023 in “Precision clinical medicine” Researchers found four genes that could help diagnose severe alopecia areata early.