June 2022 in “Frontiers in Genetics” Machine learning is effective in predicting gene functions and their relationships with diseases.
November 2025 in “Psychoneuroendocrinology” This study reported that machine learning analysis of protein profiles in hair segments achieved high accuracy in distinguishing women with non-suicidal self-injury disorder from healthy controls, suggesting hair proteomics as a promising non-invasive biomarker for stress-related psychopathology with potential clinical applications.
This theoretical research project proposes the Carnivore Follicular Integrity Framework, suggesting that animal-based diets may support hair follicle stability through various evolutionary and mechanistic pathways.
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April 2010 in “ACS Nano” This study found that about 80% of known fullerene-binding proteins rank in the top 10% of scorers for C60 docking sites, confirming the accuracy of the predictive model used.
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October 2020 in “Therapeutic drug monitoring” In this study, researchers found that targeting a tacrolimus trough level of 4–7 ng/mL after liver transplantation resulted in comparable graft and patient survival rates to higher levels, while improving liver and kidney function markers.