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3D bioprinted lung cancer models in a mouse-like structure offer a better way to study radiation effects without using live animals.

3D human skin models show promise for dermatology but face challenges in standardization and cost.

Dr. Muhammad Ahmad created a hair classification system to help improve hair restoration surgery outcomes.

An algorithm was created to simplify lip reconstruction after surgery.

The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.

Reduced alpha smooth muscle actin may cause hair loss in androgenetic alopecia.

The data set helps improve predictions of how substances are absorbed through pig skin.

New mouse models of Pemphigus show severe symptoms and need better treatments.

A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.

Different levels of shear stress affect where cells move and gather in a 3D-printed model, helping to better understand cell behavior in blood vessels.

Pharmacophore models can predict liver toxicity and central nervous system toxicity, but they have limitations and specific requirements.

The review found that current care models for PCOS are not fully effective and more research is needed, especially in low-income countries.

A 6-group geometric classification of human scalp hair is more reliable and objective for testing than an 8-group system.

Larger nail cavity sizes suggest benign tumors, while smaller ones may need further biopsy to rule out cancer.

The model accurately predicts age from saliva and buccal cells for forensic use.

Understanding skin patterns can help us learn about skin diseases and their treatments.

Better hair loss models needed for research.

The model accurately predicts hair loss severity in alopecia areata.

The 5050 MHA42MCS45 hydrogel blend is suitable for repairing load-bearing soft tissues.

Understanding hair follicle communication can help treat hair loss.

The Hair Cell Analysis Toolbox automates and improves the analysis of cochlear hair cells using machine learning.

The framework helps develop medical apps on mobile devices to reduce reliance on desktop computers.

A detailed 3D model of human skin was created to help develop artificial skin.

The device mimics human hair follicles and detects tiny forces and moments with high sensitivity.

The facial aging scale is a reliable tool for assessing skin aging and treatment effects.

SL-HyDE improves medical information retrieval accuracy without needing labeled data.

Hair can accurately predict iron levels in cattle muscle, helping diagnose mineral imbalances.

Signaling factors and gene-driven cell adhesion are crucial for wound healing and embryo development.

The study created a mouse model to mimic degenerative diseases for testing tissue repair and new therapies.