Developing a new drug can take years of research and cost millions of dollars. Still, more than 90 percent of drug candidates fail in clinical trials, with even more that never make it to the clinical stage.
Researchers introduced "Matanya," a baby-sized companion robot designed to provide emotional support to elderly individuals in home care centers by recognizing and responding to their facial expressions. Pilot studies showed that interactions with Matanya improved the mental health and well-being of elderly users, reducing loneliness and depression, and received positive feedback from caregivers, indicating its potential for broader adoption in elderly care settings.
Researchers from the University of East Anglia, Sheffield, and Leeds have created an innovative AI-based technique for analyzing heart MRI scans, potentially saving the NHS valuable time and resources while enhancing patient care.
Researchers at the University of Cambridge have created an artificially intelligent instrument that can determine four times out of five whether a person exhibiting early signs of dementia would eventually get Alzheimer's disease or not.
SS Innovations International, Inc., developer of innovative surgical robotic technologies dedicated to making world-class robotic surgery affordable and accessible to a global population, today announced that its SSi Mantra Surgical Robotic System has been installed at Baidya & Banskota Hospital in Kathmandu, Nepal marking the first time a surgical robotic system has been installed in Nepal.
Researchers from the University of Cambridge have demonstrated, in the research published in Nature Communications, that drug-resistant diseases could be identified using AI, which would greatly shorten the time it takes to make an accurate diagnosis.
United We Care, a leader in AI-powered mental healthcare solutions, unveils Stella Clinical Copilot.
Researchers introduced a cost-effective haptic feedback system for robotic surgery training, addressing the absence of tactile and force sensations in current systems. By integrating kinesthetic and tactile feedback, this novel system significantly improves surgical precision and training fidelity, making advanced robotic surgery techniques more accessible and safer for both surgeons and patients.
This study investigates the application of deep learning algorithms to automate pneumonia detection from pediatric chest X-ray images. Researchers compared custom convolutional neural networks (CNNs) with transfer learning using ResNet152V2, emphasizing fine-tuning strategies to optimize model performance.
King Faisal Specialist Hospital & Research Centre (KFSH&RC) is at the forefront of the global AI and robotics revolution.
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