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Cognitive-behavioral therapy is the best treatment for hair-pulling disorder, and combining it with other therapies could improve results.

The study found that different criteria led to different patient groups in the CombAT study compared to the MTOPS study.

The conclusion is that the risk of losing significance in meta-analysis results increases with smaller effects and more missing data, and using the median standard deviation for imputation is recommended.

The humanized AA mouse model is better for testing new alopecia areata treatments.

A standardized scoring system is needed to improve model reliability for predicting hair loss in brain tumor patients treated with proton therapy.

The study aims to create a model to predict health attributes using diverse health data from Japanese adults.

The Advanced Precipitation U-Net Model improves early hair fall detection with 92% accuracy.

The tool accurately measures hair count and size on scalps with 79.45% and 68.19% accuracy, respectively.

The new method improves accuracy in segmenting scalp tissue layers.

Hyperbranched polymer dots significantly boost hair regrowth better than minoxidil.

Megasessions in hair transplant can cover more area or increase density but need a skilled team and careful planning, and have both benefits like less downtime and risks like lower graft survival.

The models accurately predicted urticaria in Ukrainian women but struggled to differentiate between mild and severe cases based on body structure.

Gamma-ray exposure improves genome editing efficiency in mice using the i-GONAD method.

Human hair becomes weaker and stretches more easily at higher temperatures.

Panitumumab can cause excessive ear hair growth.

Bank employees' multitasking effectiveness improves with cognitive flexibility, time management, stress tolerance, motivation, and specialized training.

The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.

The machine learning model effectively assesses the severity of hair loss and could help dermatologists with treatment decisions.

AI can effectively predict COVID-19 mortality risk using patient data.

The new microrhizotron tool effectively observes and measures pepper plant roots non-destructively.

Pattern mode isolation improves the reliability and predictability of Turing patterns.

The new AI system improves remote skin condition diagnosis and access to care.

Combining genetic and physical data improves diagnosis and treatment for early-onset monogenic diabetes.

AI can improve alopecia areata diagnosis with high accuracy.

The Hair Implanter Pen increases speed and is gentle on grafts, with users mastering it after a few tries.

A deep learning model was developed to help diagnose trichothiodystrophy by analyzing hair patterns.

Combination 3 of ethnomedicinal plants from Nusa Tenggara Timur significantly increases hair-follicle thickness.