AI Identifies Long COVID Care Requirements in Hospital Patients
January 13, 2025AI identifies long COVID care needs in hospitals, highlighting patient sub-populations for tailored treatment. 🤖🏥
Using voice recognition and machine learning techniques for detecting patient-reported outcomes from conversational voice in palliative care patients.
January 13, 2025Voice recognition in palliative care shows promise for capturing patient-reported outcomes. 📊 Further research needed for improved accuracy. 🗣️
PocDoc Launches Cardiovascular Disease Screening App in West Yorkshire
January 12, 2025PocDoc introduces a cardiovascular disease screening app in West Yorkshire, enhancing access to heart health assessments. ❤️🩺
From Spectra to Signatures: Detecting Fentanyl in Human Nails with ATR-FTIR and Machine Learning.
January 12, 2025Recent research highlights the potential of using human nails to detect fentanyl. 🧪🔍 Machine learning enhances accuracy in toxicology.
Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats.
January 12, 2025Medical history can predict disease onset and aid in responding to health threats like COVID-19. 📊🩺
Assessment of decision-making with locally run and web-based large language models versus human board recommendations in otorhinolaryngology, head and neck surgery.
January 12, 2025Exploring LLMs in cancer treatment decisions 🧠💉: A study compares human recommendations with AI models in otorhinolaryngology.
Qwen-2.5 Outperforms Other Large Language Models in the Chinese National Nursing Licensing Examination: Retrospective Cross-Sectional Comparative Study.
January 11, 2025Qwen-2.5 excels in nursing exams! 📚🤖 Study shows it outperforms other models, enhancing medical education accuracy.
Insights on Healthcare Trends for 2025
January 11, 2025Healthcare trends for 2025 include AI, cybersecurity, digital therapeutics, and telehealth advancements. 📈💻🩺
Prediction of urinary tract infection using machine learning methods: a study for finding the most-informative variables.
January 11, 2025Machine learning shows promise in predicting urinary tract infections. Key factors include urine and blood test results, age, and gender. 🤖💧