research A Hybrid Transfer Learning Approach Using Obesity Data for Predicting Cardiovascular Diseases Incorporating Lifestyle Factors
Adding obesity data to machine learning models improves heart disease prediction accuracy.
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research Weakly-Supervised Hair SEM Microscope Image Segmentation Using a Priori Structure Information
The method improves hair image segmentation accuracy while reducing annotation costs.
research Mechanism of traditional Chinese medicine in the treatment of ischemic stroke by intervening ferroptosis pathway based on molecular target prediction and bioinformatics
Traditional Chinese medicine may help treat ischemic stroke by targeting specific genes and pathways.
research ANAIS DO I CONGRESSO MÉDICO DE FORMOSA - COMEF
Dutasteride is more effective and better tolerated than finasteride for hair loss treatment.
research Scalp Disorder Imaging: How Deep Learning and Explainable Artificial Intelligence are Revolutionizing Diagnosis and Treatment
Deep learning and explainable AI are improving scalp disorder diagnosis, but challenges in transparency and data quality remain.
research Enhancing Hairfall Prediction: A Comparative Analysis of Individual Algorithms and An Ensemble Method
Combining multiple algorithms predicts hair fall more accurately than using single algorithms.
research The Dark Side of the Language: Pre-trained Transformers in the DarkNet
Pre-trained Transformers need extreme retraining to perform well on DarkNet data.
research In-silico studies in herbal drugs: A review
Computational methods can speed up and improve the development and safety of herbal drugs.
research Essential oils-based nanoemulsion formulation boosts hair growth in C57BL/6 mice as compared to minoxidil 2%
The essential oils nanoemulsion promotes hair growth better than 2% minoxidil in mice.
research Clinico-epidemiological study of cutaneous changes in pregnancy at a tertiary care centre in Puducherry
Most pregnant women experience common skin changes like linea nigra and stretch marks.
research Non-small cell lung carcinoma spheroid models in agarose microwells for drug response studies
The platform effectively grows lung cancer cell spheroids for drug testing.
research Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach
Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
research HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers
"HairSentinel" accurately detects hairfall trends using simple user data, helping identify health risks early.
research BroadAMP-GPT: AI-Driven generation of broad-spectrum antimicrobial peptides for combating multidrug-resistant ESKAPE pathogens
BroadAMP-GPT effectively creates antimicrobial peptides to fight drug-resistant bacteria.
research Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.
research Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods
Machine learning can help find new ways to treat alopecia areata.
research A Study on the Development of a Web Platform for Scalp Diagnosis Using EfficientNet
A web platform was created to help diagnose scalp conditions accurately and easily.
research An Early Hair Loss Detection and Prediction Method Based on Machine Learning
Machine learning can accurately predict hair loss early, improving treatment options.
research HairLossMultinet: A Multi Scale Feature Fusion Method Using Deep Learning Approach
HairLossMultinet accurately classifies hair damage with 98% accuracy but needs a more diverse dataset for broader use.
research A Machine Learning Algorithm Applied to Trichoscopy for Androgenic Alopecia Staging and Severity Assessment
The machine learning model effectively assesses the severity of hair loss and could help dermatologists with treatment decisions.
research Editorial: Machine Learning Techniques on Gene Function Prediction Volume II
Machine learning is effective in predicting gene functions and their relationships with diseases.
research Peer Review #3 of "Computational drug repositioning based on side-effects mined from social media (v0.1)"
Reviewers criticized the study for assuming drugs with similar side-effects work the same way and questioned the validity of its findings due to potential biases and data quality issues.
research Peer Review #3 of "Computational drug repositioning based on side-effects mined from social media (v0.3)"
Reviewers criticized the study's methods and suggested focusing on drug mechanisms instead of repositioning due to social media data quality concerns.
research Peer Review #2 of "Computational drug repositioning based on side-effects mined from social media (v0.2)"
The peer review highlighted the need for clearer data handling, questioned the study's validity, and recognized improvements from the original version.
research Peer Review #1 of "Computational drug repositioning based on side-effects mined from social media (v0.1)"
Reviewers criticized the study for its assumptions, social media data collection issues, and lack of comparison to existing methods.
research Drug Repositioning: New Approaches and Future Prospects for Life-Debilitating Diseases and the COVID-19 Pandemic Outbreak
Drug repositioning offers a cost-effective, lower-risk way to treat diseases and pandemics like COVID-19.
research PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery
PandaOmics uses AI to find new disease treatment targets and biomarkers.
research Data-Driven Machine-Learning Methods for Diabetes Risk Prediction
Machine learning can effectively predict type 2 diabetes risk.
research Development and application of emotion recognition technology — a systematic literature review
Emotion recognition tech helps devices understand emotions, but more research is needed for complex situations.