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Many are open to telemedicine for hair loss if combined with in-person visits and better technology.

In this study, researchers found that hair follicle orientation in Fz6 −/− mice is disrupted and that hair may reorient itself over time through a self-organized process.

This article discusses the role of androgens in metabolic and reproductive health and reports no new experimental results; the focus is on androgen receptor activation by testosterone and 5α-dihydrotestosterone.

This study confirms that the proposed universal model for hard α-keratin structure applies to all known forms across various mammalian species.

In this study, the authors used a Bayesian Poisson - Hidden Markov Model to analyze COVID-19 cases by blood type in Europe and Africa, finding differences in hidden states and infection rates based on blood type across these regions.

This article discusses a proposed "Darwinian" model of carcinogenesis and emphasizes that cancer prevention involves more than avoiding mutagens, as gene-environment interactions are complex and non-linear.

This study used numerical models to explore the cooling power required by different scalp cooling devices to prevent chemotherapy-induced hair loss, finding that coolant temperature significantly influences scalp tissue temperatures.

This study developed finite element models to examine skin's biomechanical properties, finding that structural heterogeneities like Rete ridges and hair follicles create distinct stress and strain patterns that may influence mechanosensation and skin integrity.

In this study, researchers discovered that the HrasG12V oncogenic mutation in murine skin epithelial cells initially promotes progenitor cell renewal but later leads to a balanced differentiation, stabilizing clone growth.

In this study, researchers observed that oncogenic HrasG12V in single murine epidermal cells leads to an initial increase in progenitor cell renewal, but ultimately results in balanced cell fate choices that limit clone growth.

This study describes a follicular automaton model that simulates human hair cycles and may replicate hair pattern evolution seen in diffuse or androgenetic alopecia.

This study used machine learning models to analyze PCOS symptoms for early diagnosis, finding Support Vector Machine and VGG16 algorithms achieved high accuracy rates of 94.44% and 98.29% respectively.

This study found that in a mouse model of Leigh syndrome, rapamycin alters brain proteome and may extend survival by targeting protein kinase C.

This review discusses how recent studies use models and experiments to understand immune system signaling, but it reports no new clinical findings; the authors suggest strategies for improving these models.

This study introduces a modular fiber model to investigate how changes in microstructural properties of wool affect its critical buckling load, highlighting potential uses and areas needing further research in wool fiber biophysics.

This article reviews mammalian skin epidermis as a model for studying stem cell regulation, noting the utility of in vitro and ex vivo platforms, but it reports no new empirical findings.

This study reports that deep learning models, particularly CNN and FCN, achieved high accuracy in diagnosing scalp and skin disorders, suggesting potential for improved diagnostic systems with further advancements.

This study found that ensemble machine learning models effectively predict hair fall by combining the strengths of individual algorithms, leading to higher accuracy, precision, and recall in identifying hair and non-hair fall instances compared to single algorithms.

The researchers in this experimental study developed a thermodynamic model using the Peng-Robinson equation of state to optimize gas antisolvent system conditions for controlling finasteride particle size, aiming to reduce experimental trials and precisely identify precipitation pressures across different temperatures.

This study found that among various predictive models for baldness risk, Random Forest Regression performed best with the lowest mean squared error and highest R², indicating strong predictive accuracy, especially with complex datasets, while Linear Regression was better suited to simpler datasets.

In this retrospective study, researchers developed machine learning models to predict mortality risk among 7115 COVID-19 patients in Iran, finding that the random forests model performed best with 96% accuracy and identified factors like intubation and SpO2 as significant predictors.

In this study, mathematical analysis suggested that a 30°-sapphire blade caused the least tissue injury during hair restoration, while a rectangular blade caused the most.

This review compares animal and human skin characteristics in in vitro permeation studies but reports no new results, highlighting variations and the need for better model correlations.

This review covers the recent advances in understanding how Turing models may explain various morphogenetic processes, but it reports no new experimental findings.

In this study, Gaussian process regression models combined with Grey Wolf optimization were used to predict and optimize phenolic and flavonoid content extraction from Carthamus caeruleus L. rhizomes, showing high accuracy and helping improve understanding and extraction processes through a new interactive tool.

This review explores the biology of wool follicles and suggests their potential use as research models in modern biology, but it reports no new findings.

In this study, researchers devised a stochastic hair growth model influenced by regular haircuts, using a process that undergoes linear growth subject to random resets, and used it to theoretically determine an ideal haircut routine.

This study found that Cacumen platycladi extract significantly promoted hair growth and reduced dihydrotestosterone levels by inhibiting 5α-reductase activity in an androgen-sensitive mouse model.

This review explores the mechanisms of adult stem cell self-renewal, using skin as a model, and reports no new results but raises important unanswered questions in the field.

This study found that a novel skin patch combining extracellular matrix and ciprofloxacin promotes advanced wound healing and skin regeneration in mouse models of infected wounds.