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Deep Learning in Healthcare: Challenges, Applications, and Future Directions

Marktechpost

Biomedical data is increasingly complex, high-dimensional, and heterogeneous, encompassing sources such as electronic health records (EHRs), imaging, -omics data, sensors, and text. In healthcare, NLP is instrumental in managing EHRs, which compile extensive medical data across patient histories.

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How AI Innovation Can Break Down Barriers in the Crisis of Late Diagnosis of Autism in Children

Unite.AI

In contrast, lack of or delayed treatment increases the likelihood of lifelong, comorbid mental health conditions , while all-cause medical costs are approximately double for children who experience a longer time to diagnosis compared with a shorter time to diagnosis. are unacceptably common. years later than boys.

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AI Technology NYUTron Accurately Predicts Health Outcomes

NYU Center for Data Science

NYUTron , the large language model (LLM), is able to read physicians’ notes and estimate patients’ risk of death, length of hospital stays, and other health factors. Physicians often write in individualized language, and the data reorganization required to compile the information into neat tables is time-consuming.

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Chatbot therapy is risky. It’s also not useless.

Flipboard

. | StudioM1/Getty Images Getting AI to improve mental health outcomes is not as simple as firing up ChatGPT. I was fortunate: My full-time job included health insurance. I lived in an area with many mental health professionals, and I had the means to consider therapists who were out of network.

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Machine Learning Turns Up COVID Surprise

Flipboard

But health records tell a different story, full of doctors’ notes and patient histories, vital signs and test results, potentially spanning weeks of a stay. In health studies, all of that data is multiplied by hundreds of patients. It’s up to us to figure out how to best manage complications that arise from it,” he said.

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Revolutionizing Healthcare: Exploring the Impact and Future of Large Language Models in Medicine

Unite.AI

As noted in the Healthcare Information Management and Systems Society global conference and other notable events, companies like Google are leading the charge in exploring the potential of generative AI within healthcare. However, their deployment must be carefully managed to avoid reliance on AI without proper human oversight.

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Large Language Models in Telemedicine and Remote Care

John Snow Labs

In this way, LLMs optimize diagnostic processes, refine virtual consultations, and improve the management of electronic health records (EHRs). LLMs play a crucial role in managing comprehensive patient records, ensuring patients receive personalized and culturally sensitive care, regardless of location.