research Sentiment Analysis and Natural Language Processing Using Reddit Data to Evaluate Patient Opinions on Hair Loss Therapeutics
People on Reddit generally have positive opinions about hair loss treatments.
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research Beyond Hair Loss: Exploring the Evolution of Androgenetic Alopecia Research Based on Text Mining and Bibliometrics
Data visualization tools are crucial for understanding and advancing androgenetic alopecia research.
research Deep Skin Diseases Diagnostic System With Dual-Channel Image and Extracted Text
The AI model DIET-AI effectively diagnoses skin diseases as well as doctors.
research Exploring Diachronic Changes of Biomedical Knowledge Using Distributed Concept Representations
The document concluded that biomedical knowledge changes over time and the study evaluated a new method to track these changes.
research Beyond Hair Loss: Exploring the Evolution of Androgenetic Alopecia Research Based on Text Mining and Bibliometrics
Visualizing data helps guide future androgenetic alopecia research and policies.
research The Dark Side of the Language: Syntax-Based Neural Networks Rivaling Transformers in Unseen Sentences
Syntax-based neural networks can match Transformers in handling unseen sentences.
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 AnnoPharma: Detection of Substances Responsible for Adverse Drug Reactions by Annotating and Extracting Information from MEDLINE Abstracts
AnnoPharma effectively identifies substances causing adverse drug reactions in medical abstracts.
research Peer Review of Computational Drug Repositioning Based on Side-Effects Mined from Social Media
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 LabeledIn: Cataloging Labeled Indications for Human Drugs
Researchers created LabeledIn, a detailed list of drug uses, showing the importance of human input in making such lists.
research Weakly Supervised Learning of Biomedical Information Extraction from Curated Data
The method can effectively extract biomedical information without needing expert annotation, performing better than previous models.
research Aspect-Level Drug Reviews Sentiment Analysis Based on Double BiGRU and Knowledge Transfer
A model called PM-DBiGRU was developed for analyzing sentiments in drug reviews, and it performed better than other models, but struggled with complex sentences and situations requiring background knowledge.
research Generative Adversarial Networks for Anonymous Acneic Face Dataset Generation
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
research Drug Repositioning: Current Approaches and Their Implications in the Precision Medicine Era
Drug repositioning is becoming more targeted and efficient with new technologies, offering personalized treatment options and growing interest in the field.
research A Machine Learning and Network Framework to Discover New Indications for Small Molecules
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.
research Computational Derivation of a Molecular Framework for Hair Follicle Biology from Disease Genes
The research provides a gene-based framework for hair biology, highlighting the Hippo pathway's importance and suggesting links between hair disorders, cancer pathways, and the immune system.
research Optimizing Skin Disease Diagnosis: Harnessing Online Community Data With Contrastive Learning and Clustering Techniques
Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
research Androgenic Alopecia: Cross-Talk Between Cell Signal Transduction Pathways
Hair loss in Androgenetic alopecia (AGA) is due to altered cell sensitivity to hormones, not increased hormone levels. Hair growth periods shorten over time, causing hair to become thinner and shorter. This is linked to miscommunication between cell pathways in hair follicles. There's also a change in gene expression related to blood vessels and cell growth in balding hair follicles. The exact molecular causes of AGA are still unclear.
research Kalya Research: Complementary and Alternative Medicine Virtual Research Assistant from Biomedical Literature
Kalya Research is an AI tool that effectively finds and analyzes alternative medicine literature, saving researchers time.
research Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs
Long-COVID has diverse, long-term health impacts, especially in young people.
research Discerning Patient Perspectives Towards Specific Treatments of Alopecia Areata Using Artificial Intelligence
Patients using social media have mixed feelings about alopecia treatments, noting hair growth but also frustration with treatment recurrence.
research Social Media for Arthritis-Related Comparative Effectiveness and Safety Research and the Impact of Direct-to-Consumer Advertising
Social media can help compare the effectiveness and safety of new arthritis medications.
research Using Artificial Intelligence to Analyze Publicly Available Social Media Posts to Understand Patient Perspectives Toward Specific Treatments of Alopecia Areata
Patients generally feel positive about alopecia areata treatments, but emotions vary by treatment type.
research Who Do We Invent For? Patents by Women Focus More on Women’s Health, but Few Women Get to Invent
Women inventors focus more on women's health, but there are few of them.
research Network Pharmacology Reveals Curcuma Aeruginosa Roxb. Regulates MAPK and HIF-1 Pathways to Treat Androgenetic Alopecia
Curcuma aeruginosa Roxb. may help treat hair loss by affecting specific biological pathways.
research Quantitative and Qualitative Analysis of Individual Experiences Post Botulinum Toxin Injection - United Kingdom Survey
Most UK survey participants had negative side effects from botulinum toxin injections, with many not fully recovering physically, emotionally, or financially.
research Peer Review of Computational Drug Repositioning Based on Side-Effects Mined from Social Media
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 of Computational Drug Repositioning Based on Side-Effects Mined from Social Media
Reviewers suggested the study on finding new drug uses through social media side-effects needs better methods and clearer limitations.
research Peer Review of Computational Drug Repositioning Based on Side-Effects Mined from Social Media
The study improved and was accepted despite initial concerns about data clarity, methodology, and potential overfitting.
research Peer Review of Computational Drug Repositioning Based on Side-Effects Mined from Social Media
Reviewers criticized the study's methods and suggested focusing on drug mechanisms instead of repositioning due to social media data quality concerns.