Nine Tasks and One Big Challenge for Shared Care Records in 2024

Opinion Article by Mark Hindle, vice president EMEA, Orion Health,.
It's going to be a busy year in the shared care records space. NHS leaders, ShCRs and their suppliers are going to have plenty of work in hand to drive adoption, improve maturity, share data across boundaries, and start thinking about how to extend the use of ShCR information to system leaders and patients.

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Novel AI Platform Matches Cardiologists in Detecting Rheumatic Heart Disease

Artificial intelligence (AI) has the potential to detect rheumatic heart disease (RHD) with the same accuracy as a cardiologist, according to new research demonstrating how sophisticated deep learning technology can be applied to this disease of inequity. The work could prevent hundreds of thousands of unnecessary deaths around the world annually.

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AI Helps Coronary CT Angiography and Accelerates the Development of Precision Medicine

This review was jointly published by Prof. Long-Jiang Zhang (Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University) and Prof. Christian Tesche (Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina and Department of Cardiology, Munich University Clinic, Ludwig-Maximilian-University).

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Aston University AI Project Aims to Make International Health Data Sharing Easier

Aston University is to explore the use of AI to improve sharing health data internationally.

Dr Sergei Sokolovski of the University's Aston Institute of Photonic Technologies has been awarded €317,500 to work on a European-wide project.

Called BETTER (Better real-world health data distributed analytics research platform) the spans16 academic, medical and industrial partners.

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Clinical Predictive Models Created by AI are Accurate but Study-Specific

In a recent study, scientists have been investigating the accuracy of AI models that predict whether people with schizophrenia will respond to antipsychotic medication. Statistical models from the field of artificial intelligence (AI) have great potential to improve decision-making related to medical treatment. However, data from medical treatment that can be used for training these models are not only rare, but also expensive.

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Accelerating How New Drugs are Made with Machine Learning

Researchers have developed a platform that combines automated experiments with AI to predict how chemicals will react with one another, which could accelerate the design process for new drugs.

Predicting how molecules will react is vital for the discovery and manufacture of new pharmaceuticals, but historically this has been a trial-and-error process, and the reactions often fail.

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Creating Exam Questions with ChatGPT

For the study, the UKB (Universitätsklinikum Bonn) researchers created two sets of 25 multiple-choice questions (MCQs), each with five possible answers, one of which was correct. The first set of questions was written by an experienced medical lecturer, the second set was created by ChatGPT. 161 students answered all questions in random order.

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AI-Driven Eye Exams Increase Screening Rates for Youth with Diabetes

A Johns Hopkins Children’s Center study of children and youth with diabetes concludes that so-called autonomous artificial intelligence (AI) diabetic eye exams significantly increase completion rates of screenings designed to prevent potentially blinding diabetes eye diseases (DED). During the exam, pictures are taken of the backs of the eyes without the need to dilate them, and AI is used to provide an immediate result.

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Draft Digital Health #Rewired24 Programme Published

12 - 13 March 2024, Birmingham, UK.
Digital Health has published the draft programme for the big five stages at Rewired24, the UK's biggest and best health IT and digital health event.

Each of the five main stages run across the two-days of Rewired24 which will run at the NEC Birmingham, packed with original keynotes, inspiring NHS case studies, panel sessions and lively Rewired debates.

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eHealth Network Guideline on Hospital Discharge Report

The Member States in the eHealth Network have adopted these supplementary clauses to the general guidelines for the electronic exchange of health data under Cross-Border Directive 2011/24/EU to support the exchange of Hospital Discharge Report for continuity of care in a cross-border setting. The Hospital Discharge Guideline builds on the foundations laid out by the Patient Summary and the ePrescription Guidelines (including datasets and code systems). The eHealth Network guidelines build a set of guidelines that should be seen as complementing each other in different use cases and are operating under the umbrella of the General Guidelines.

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