yesilscience - Yesil Science

[Responsible use of AI and robotics in medicine : Opportunities, challenges and perspectives for otorhinolaryngology].

[Responsible use of AI and robotics in medicine : Opportunities, challenges and perspectives for otorhinolaryngology].

AI and robotics in medicine: Transforming practices with ethical challenges. Key principles: transparency, shared responsibility, legitimacy. 🤖⚕️

January 16, 2026

Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial.

🏋️ Fitness & Sports 🤖 Machine Learning 🩺 Preventive Medicine 🌐 Telehealth

Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial.

AI telerehabilitation boosts exercise capacity in hypertension patients: 62.77m improvement in 6MWD after 8 weeks! 📈💪

January 16, 2026

Artificial intelligence-driven clustering for phenotyping life-threatening prehospital trauma.

🚑 Critical Care 🤖 Machine Learning

Artificial intelligence-driven clustering for phenotyping life-threatening prehospital trauma.

AI clusters trauma patients into three phenotypes, revealing 93.1% mortality in T-1 group. Key for emergency care! 🚑📊

January 16, 2026

Scoping review of regulatory transparency in AI-based radiology software: analysis of PMDA-approved SaMD products.

⚖️ AI Ethics 🥗 Nutrition 🛌 Palliative Care 🧬 Rare Diseases 🏢 Work Health

Scoping review of regulatory transparency in AI-based radiology software: analysis of PMDA-approved SaMD products.

Exploring AI in radiology: 2026 review on PMDA-approved software reveals transparency gaps. 📊🤖

January 15, 2026

AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging.

🖼️ Computer Vision 🤖 Machine Learning 🎗 Oncology

AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging.

AI-driven deep learning enhances ampullary lesion diagnosis: 92.2% accuracy, 83.3% sensitivity for high-grade dysplasia. 📊🔍

January 15, 2026

Concerns Over Slow Adoption of Technology in NHS, Says Health Secretary

💼 Health Entrepreneurship 🤖 Machine Learning 📰 News 🌍 Public Health

Concerns Over Slow Adoption of Technology in NHS, Says Health Secretary

NHS faces challenges in adopting technology, warns Health Secretary. Slow progress may hinder efficiency and patient care. 📉💻

January 14, 2026

ViSQA: A benchmark dataset and baseline models for Vietnamese spoken question answering.

🤖 Machine Learning 🗣️ Speech Recognition

ViSQA: A benchmark dataset and baseline models for Vietnamese spoken question answering.

ViSQA: First Vietnamese Spoken Question Answering Benchmark with 13,000+ pairs, revealing ASR errors impact on performance. 📊🔍

January 14, 2026

Echocardiographic Evaluation in Children with Post-Acute Sequelae of SARS-CoV-2 Infection Using Deep Learning.

🧠 Digital Therapeutics 🤖 Machine Learning 🌍 Public Health

Echocardiographic Evaluation in Children with Post-Acute Sequelae of SARS-CoV-2 Infection Using Deep Learning.

Echocardiography in Kids with PASC: Deep Learning Achieves 96.6% Accuracy! 🫀📊

January 14, 2026

New CEO Appointed for Health Data Research Service

⚖️ AI Ethics 🔐 Blockchain 💼 Health Entrepreneurship 📰 News 🌍 Public Health

New CEO Appointed for Health Data Research Service

New CEO for Health Data Research Service appointed. Dr. Melanie Ivarsson aims to streamline medical research data access. 📊👩‍⚕️

January 14, 2026

WSSM: A Weakly Supervised Oral Mucosal Disease Segmentation Model Based on Multi-Task Collaboration.

🖼️ Computer Vision 🌟 Dermatology 🤖 Machine Learning

WSSM: A Weakly Supervised Oral Mucosal Disease Segmentation Model Based on Multi-Task Collaboration.

Innovative WSSM model enhances oral mucosal disease segmentation accuracy by 6.06% using multi-task collaboration. 📊🦷

January 14, 2026

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Author: yesilscience

[Responsible use of AI and robotics in medicine : Opportunities, challenges and perspectives for otorhinolaryngology].

Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial.

Artificial intelligence-driven clustering for phenotyping life-threatening prehospital trauma.

Scoping review of regulatory transparency in AI-based radiology software: analysis of PMDA-approved SaMD products.

AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging.

Concerns Over Slow Adoption of Technology in NHS, Says Health Secretary

ViSQA: A benchmark dataset and baseline models for Vietnamese spoken question answering.

Echocardiographic Evaluation in Children with Post-Acute Sequelae of SARS-CoV-2 Infection Using Deep Learning.

New CEO Appointed for Health Data Research Service

WSSM: A Weakly Supervised Oral Mucosal Disease Segmentation Model Based on Multi-Task Collaboration.

Improving consciousness assessment through neuroadaptive artificial intelligence and quantum-enhanced brain-computer interfaces.

Creativity as a core competency in medical education: the art of medicine.

A Pilot Study to Evaluate Artificial Intelligence-Driven Early Retrieval of Medical Histories in the Emergency Department.

Insufficient reporting quality in large language model studies in the field of radiology.

Merck Introduces ChemiSphere® App for Enhanced Lab Data Access

BioPathNet: A New AI Tool for Analyzing Biomedical Data Networks

Leveraging Digital Technology and Artificial Intelligence to Describe the Real-World Belgian Chronic Lymphocytic Leukemia Patient Population: The BE-CLLEAR Study.

DiaCardia: AI Model for ECG-Based Prediabetes Detection

Safety and user perception of general-purpose large language models in pediatric healthcare: Evaluations of ChatGPT by doctors and parents.

DHSC and NHSE Commit to £7.4 Billion Digital Investment by 2030