research DrugNet: Network-based drug–disease prioritization by integrating heterogeneous data
DrugNet effectively identifies new uses for existing drugs and may save resources in drug development.
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research Pruritic Rash with Actinic Keratosis and Impending Exfoliation in a Patient with Hypertension Managed with Minoxidil
Minoxidil caused a severe rash in a patient, which improved after stopping the drug.
research The Drug Reboot: Finding New Life in Old Formulations
Repurposing existing drugs can quickly and cheaply find new treatments for diseases.
research PO.8.170 Drug-induced lupus or systemic lupus erythematosus after experimental COVID-19 therapy: difficulties in differential diagnosis
Distinguishing drug-induced lupus from systemic lupus is challenging and requires careful monitoring.
research Coexistence of alopecia areata and fixed drug eruption: An uncommon isotopic phenomenon?
A rare skin reaction occurred when a man took paracetamol, causing a new rash in an area already affected by hair loss.
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 Impact of artificial intelligence on healthcare
AI is revolutionizing healthcare by improving diagnosis, treatment, and monitoring, but still needs close supervision.
research Eyelash trichomegaly: review of congenital, acquired, and drug‐associated etiologies for elongation of the eyelashes
The document concludes that eyelash trichomegaly, which is the abnormal growth of eyelashes, can be present from birth, caused by diseases, or result from certain medications.
research Data-driven strategies for drug repurposing: insights, recommendations, and case studies
Drug repurposing can speed up and reduce costs in drug discovery, especially for cancer treatment.
research Real-world pharmacovigilance insights into drug-induced risk of alopecia
64 drugs can cause hair loss, needing better monitoring and updated labels.
research 596 Application of an artificial intelligence (AI) photographic device to track platelet-rich plasma treatment outcomes in females with alopecia
An AI photographic device effectively tracked hair growth improvements in women treated for hair loss.
research Psychotropic Medication and Drug-Related Alopecia
Some psychiatric medications can cause reversible hair loss.
research Drug Repurposing against KRAS Mutant G12C: A Machine Learning, Molecular Docking, and Molecular Dynamics Study
Afatinib, neratinib, and zanubrutinib could be effective against KRASG12C-mutant tumors.
research Drug Repurposing: Accelerating New Therapeutic Discoveries from Old Molecules (1990 – 2025)
Drug repurposing finds new uses for old drugs quickly and cheaply.
research Drug Repurposing: Accelerating New Therapeutic Discoveries from Old Molecules (1990 – 2025)
Repurposing existing drugs can quickly and cheaply find new treatments.
research Psoriasis and Alopecia: Unveiling the Links
Psoriasis patients are more likely to develop alopecia areata due to complex autoimmune interactions.
research Artificial intelligence: revolutionizing robotic surgery: review
AI in robotic surgery improves precision and safety but faces cost and ethical challenges.
research Knowledge Mapping of Drug Repositioning’s Theme and Development
Drug repositioning can save time and money but needs more support.
research Advancements in Drug Repurposing: Examples in Psychiatric Medications
Old psychiatric drugs are increasingly being used for new purposes, and technologies like SmartCube® help create new drugs.
research Agglomerative clustering-based drugs graded for the risk signals of drug-induced cognitive disorder: a study on the FAERS database
Finasteride is high-risk for cognitive disorders, while Carbidopa/Levodopa, Topiramate, and Clonazepam are moderate-risk.
research Artificial Intelligence in Dermatology: Assessing Predictability in Clinical Diagnosis
The AI showed high accuracy in diagnosing skin conditions but needs improvement for immunological and infectious disorders.
research Multiple crosslinked, self-healing, and shape-adaptable hydrogel laden with pain-relieving chitosan@borneol nanoparticles for infected burn wound healing
The hydrogel effectively treats infected burn wounds by reducing pain and preventing infection.
research Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
research Ultra-Performance Liquid Chromatography with Electrospray Ionization Tandem Mass Spectrometry for the Determination of Ketoconazole in Anti-Dandruff Shampoo
The method accurately measures the amount of ketoconazole in anti-dandruff shampoo and cream, and can also be used to monitor the drug in human plasma.
research Drug Repurposing for Rare Diseases
Drug repurposing offers a faster, cheaper way to find treatments for rare diseases.
research Cutaneous manifestations of COVID-19 and vaccines for its prevention: a review of the existing literature
COVID-19 and its vaccines can cause various skin issues due to viral effects, immune responses, and stress.
research Patient Perspectives regarding Artificial Intelligence-Driven Trichoscopy for Alopecia Evaluation
Patients found AI helpful for alopecia diagnosis but want it to support, not replace, doctors.
research Integrated edge information and pathway topology for drug-disease associations
iEdgePathDDA effectively finds new drug-disease links, outperforming other methods.
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 A weighted non-negative matrix factorization approach to predict potential associations between drug and disease
WNMFDDA effectively predicts drug-disease associations.