"Bider" markings in Dun Mongolian horses are caused by a complex network of genes and pathways.
1 citations
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November 2021 in “World Family Medicine Journal /Middle East Journal of Family Medicine” Different specialties at different hospitals use various consultation models.
12 citations
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November 2014 in “PLOS Computational Biology” The study concluded that hair growth in mice is regulated by a stable interaction between skin cell types, and disrupting this can cause hair loss.
July 2024 in “International Journal of Molecular Sciences” MicroRNAs could help assess and manage multiple chronic diseases.
2 citations
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March 2023 in “Research Square (Research Square)” Forensic DNA phenotyping faces challenges due to inconsistent terminology, limited genetic understanding, and debates over technology and models.
Moles may stop growing due to cell cooperation, not just because of individual cell aging.
June 2026 in “Mendeley Data” June 2026 in “Mendeley Data”
September 2023 in “Reports of Vinnytsia National Medical University” The models accurately predicted urticaria in Ukrainian women but struggled to differentiate between mild and severe cases based on body structure.
The study aims to create a model to improve personalized and preventive health care.
June 2025 in “International Journal of Computational Intelligence Systems” The TPAP method effectively categorizes androgenetic alopecia patients with high accuracy, but needs real-world validation.
3 citations
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March 2023 in “bioRxiv (Cold Spring Harbor Laboratory)” Neurospectrum effectively analyzes neural signals to predict and identify brain activity patterns better than traditional methods.
2 citations
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November 2018 in “Indian Journal of Pharmaceutical Education” The developed model can predict effective 5-alpha-reductase enzyme inhibitors.
6 citations
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February 2025 in “Scientific Reports” MEGA PROTAC improves prediction and ranking of protein complexes better than existing methods.
67 citations
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July 2000 in “Proceedings of the National Academy of Sciences” The model accurately simulates human hair growth and hair loss patterns.
1 citations
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August 2012 in “Research in Pharmaceutical Sciences”
60 citations
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December 1998 in “Clinical Pharmacology & Therapeutics” Both drugs lower DHT levels, with GI198745 being more effective.
10 citations
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January 2007 Trademark law should focus on context, not rigid rules, for clearer decisions.
January 2018 in “Computational Toxicology” Pharmacophore models can predict liver toxicity and central nervous system toxicity, but they have limitations and specific requirements.
34 citations
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December 1991 in “Annals of the New York Academy of Sciences” The conclusion is that small hair follicles cause baldness in macaques, and treatments like antiandrogens and minoxidil can prevent hair loss and promote regrowth.
April 2023 in “JMIR Research Protocols” The study aims to create a model to predict health attributes using diverse health data from Japanese adults.
822 citations
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January 2021 in “Genome biology” scMC effectively separates biological signals from technical noise in single-cell genomics data.
5 citations
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January 2018 in “Interdisciplinary sciences: computational life sciences” Accurate protein modeling can help develop new treatments for prostate cancer and other diseases.
79 citations
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July 2022 in “Sensors” Machine learning can effectively predict type 2 diabetes risk.
1 citations
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May 2018 in “Psychology, Health & Medicine” The two-factor model fits better for Chinese patients' understanding of illness causes than the original four-factor model.
November 2020 in “Journal of Pharmaceutical Sciences” The decision tree can predict drug absorption issues with good accuracy but needs more validation and adjustments for other factors.
5 citations
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March 2022 in “Frontiers in Endocrinology” A model using hormone levels, cycle length, and BMI can help identify PCOS in Chinese women but isn't for screening teens.
9 citations
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January 2017 in “International Journal of Trichology” No current system perfectly classifies male-pattern hair loss, indicating a need for a new system for better diagnosis and treatment.
July 2024 in “Journal of Investigative Dermatology” Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.