Search

everythingexperts & clinicslearnresearchcommunity

for

Search:↓

ATR-FTIR spectroscopy could help monitor alopecia areata treatment response non-invasively.

Gap junctions help control feather pattern formation in chickens.

Machine learning can predict symptoms and quality of life in chronic skin disease patients using smartphone app data, and shows that app use varies with patient characteristics.

Genetic and lifestyle factors influence skin and hair aging, and prediction models can help assess aging and cosmetic treatments.

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

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

Predictive computational analyses have evolved biopower by using technology to track and predict individual and group behaviors.

The model can predict website market shares by identifying competition among them.

A new model can predict drug-disease links well, helping drug research.

The model successfully predicted new uses for existing drugs, like using certain hormonal and heart medications for respiratory and Parkinson's diseases, and a cancer drug for diabetes.

A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.

Mathematical modeling can improve regenerative medicine by predicting biological processes and optimizing therapy development.

Understanding chaos and control mechanisms in disease can improve diagnosis and prediction in medicine.

CEC levels may be a useful marker for predicting prostate cancer progression.

The conclusion is that measuring how drugs partition into artificial sebum is important for predicting their delivery into hair and sebaceous follicles, and it provides better information than traditional methods.

The study found that diseases can be grouped by symptoms and that the accuracy of predicting disease-related genes varies with the data source.

Forensic DNA Phenotyping can now better predict appearance, ancestry, and age from DNA, but more research is needed for precise police use.

Obesity and lifestyle strongly affect heart aging.

A new test using NOS2 and CCL27 genes can better diagnose and treat psoriasis and eczema.

It's hard to predict how much worse urinary symptoms will get over time.

Reliable machine learning in medical imaging needs bias checks and data drift detection for consistent performance.

The research found that for a typical hair density, about 11 square centimeters of donor scalp is needed to get 800 hair grafts for transplantation.

The study found an efficient method to extract antioxidants from Hibiscus leaves.

Melanoma risk tools need improvement, a gene mutation causes a hair disorder that might be treated by managing cell stress, a potential therapy for a skin-ear disorder involves blocking cell channels, skin wrinkling may indicate lung aging regardless of smoking, and oxidative stress might contribute to common baldness.

Parental uveitis increases offspring's risk and severity of autoimmune eye disease.

Genetic markers can help predict ear shapes for forensic use.

Mitochondrial features can predict colorectal cancer outcomes and improve immunotherapy.

Organoids can revolutionize medicine by modeling diseases and aiding in personalized treatments.

The ShorT method can detect and help reduce bias in medical AI by identifying shortcut learning.

Gene expression in hair follicles can help diagnose methamphetamine use disorder.