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This essay discusses the author's views on establishing a successful academic laboratory and reports no new research findings.

This study introduces PROMETHEUS, a framework that organizes causal claims from scientific texts into navigable and persistent "causal atlases," enhancing research by highlighting localized evidence, agreement, and contradictions within complex data sets.

This abstract provides no results, as it pertains to a presentation on determining hip muscle forces using an EMG-to-force processing model.

This study developed and validated tissue-specific and age prediction models using epigenetic markers, achieving up to 83.69% correct classification for tissue origin and a median absolute error of ±3.66 years for age estimation.

This study applied a prediction model based on five SNPs to Russian males with male pattern hair loss, finding a significant association between the AR genomic region and high dihydrotestosterone levels in these patients.

This review discusses the limitations of animal models, particularly mice, in accurately predicting human skin wound healing outcomes and emphasizes understanding species-specific differences in skin characteristics for better translation to clinical settings.

This study highlights that while advances in dermatology, such as biologics and JAK inhibitors, have improved treatments for conditions like atopic dermatitis and psoriasis, challenges remain, including issues with lasting efficacy and the need for more personalized therapies.

This study found that increased ovarian volume is associated with markers of insulin resistance in women with polycystic ovary syndrome, while follicle number was not linked to metabolic risk.

This study found that acanthosis nigricans in the knuckles correlates with higher insulin and HOMA-IR values, potentially serving as an early, accessible marker for insulin resistance even without excess weight.

This study on feather pattern formation in chicken skin found that inhibiting gap junctional intercellular communication can lead to the emergence of new feather buds in specific spatial patterns, suggesting that GJIC may facilitate Turing-type periodic patterning by propagating inhibitory signals over long distances.

This study reported that AutoML effectively modeled itching and pain development, as well as app use, in patients with chronic eczema or psoriasis using a smartphone monitoring app, revealing that factors like BMI, age, and disease activity significantly influenced app engagement.

This article examines the emergence of predictive analytics with big data and concludes that Foucault's concept of biopower is now a hybrid involving various technologies to monitor and model behavior and risk.

This study developed a two-step diagnostic model using transcriptome biomarkers from hair follicles to improve the accuracy of methamphetamine use disorder diagnosis, achieving high prediction accuracy in distinguishing non-recovered and almost-recovered patients from healthy controls.

This study reports that an Explainable AI-based hair health prediction system using a novel hybrid model outperformed traditional machine learning methods, achieving high accuracy in predicting key factors and providing personalized recommendations.

In this study, deep learning models accurately predicted gene expression in whole slide images of colorectal cancer, with convolutional neural networks outperforming transformer and graph-based approaches in spatial RNA pattern prediction.

In this study, researchers identified six novel prognostic biomarkers for bladder cancer and developed a predictive model that effectively stratifies patients into high-risk and low-risk groups based on immune cell infiltration differences and gene expression.

This study developed a molecular systems architecture to map the complex interactions between mesenchymal stromal cells and their microenvironment, providing a framework for future predictive models that could enhance therapeutic strategies and reduce adverse effects.

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.

In this study, researchers measured the solubility of Minoxidil in supercritical CO₂ under various temperature and pressure conditions and created models to estimate solubility based on different predictive approaches.

In this review, the authors examined the role of the extracellular matrix in cancer progression and highlighted how decellularization techniques are used to create biomimetic tumor models, discussing the potential for personalized and predictive cancer treatments using advanced biomaterials combined with AI and machine learning.

This study observed distinct plasma miRNA profiles in alopecia areata, identifying several miRNAs downregulated in both mild and severe forms; machine learning models demonstrated strong predictive accuracy, and kinase inhibitors were suggested as promising therapeutic targets based on pathway analysis.

In this study, combining flutamide with finasteride showed additive effects in reducing tumor and prostate growth in a mouse model predictive of androgen-sensitive prostate cancer.

This study applied a novel Cox regression subsampling method to massive datasets, demonstrated using UK-biobank colorectal cancer data, effectively reducing computation time and memory usage while building a risk-prediction model under certain conditions involving right-censored and potentially left-truncated data with rare events.

This study used artificial neural networks to predict hair loss by analyzing factors like gender and zinc deficiency, suggesting neural networks may effectively model hair loss prediction.

This study identified four ferroptosis-related genes, SLC40A1, LCN2, CREB5, and SLC7A11, as potential diagnostic markers for alopecia areata, revealing reduced expression in affected patients compared to controls, with a predictive model showing high accuracy in differentiating the condition.

The model can effectively identify good quality skin images but needs more testing for real-world use.

This review summarizes advancements in forensic DNA phenotyping for appearance, ancestry, and age prediction from crime scene samples, reporting no new research findings but highlighting areas needing further research and validation.

This study developed a new method for analyzing multivariate time-series data that successfully predicts website competition dynamics and outperforms conventional methods in identifying and predicting competitive structures.

This study developed a model using cardiovascular radiomics to estimate biological heart age, finding obesity and other health factors strongly correlated with accelerated heart aging.

This study developed a multiscale model to understand human hair fiber mechanics and found that the yield stress decreases linearly with temperature, supported by both simulations and experimental stretching of hair fibers.