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DMEA nova Award: Wanted - Visionary Solutions for Digital Healthcare

9 - 11 April 2024, Berlin, Germany.
The DMEA nova Award is being presented at DMEA 2024 for the first time. The award honours a digital health startup for an outstanding idea or solution aimed at advancing digital healthcare.

Startups have become an indispensable part of the digital health industry. Not only are they aspiring enterprises, they are also exceptionally creative, combining traditional medical care with state-of-the-art technology.

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American College of Radiology Releases Joint Statement on the Use of AI Tools in Radiology

The American College of Radiology® (ACR®), working in close collaboration with four other radiology societies from around the world, have issued a joint statement on the development and use of artificial intelligence (AI) tools in radiology. This groundbreaking joint statement is openly available in ACR's Journal of the American College of Radiology, published by Elsevier.

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Autonomous Synthesis Robot Uses AI to Speed Up Chemical Discovery

Chemists of the University of Amsterdam (UvA) have developed an autonomous chemical synthesis robot with an integrated AI-driven machine learning unit. Dubbed 'RoboChem', the benchtop device can outperform a human chemist in terms of speed and accuracy while also displaying a high level of ingenuity.

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Northern Care Alliance Deploys Digital Pathology with Sectra

The trust's Oldham laboratory has completed technical go-live, with its Salford site also set to follow. Collectively the laboratories provide a wide range of general and specialist pathology services that support diagnoses for patients in the region. This includes one of the largest dermatology departments in the country, and gynaecology services that cover six hospitals.

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AI Harnesses Tumor Genetics to Predict Treatment Response

In a groundbreaking study published on January 18, 2024, in Cancer Discovery, scientists at University of California San Diego School of Medicine leveraged a machine learning algorithm to tackle one of the biggest challenges facing cancer researchers: predicting when cancer will resist chemotherapy.

All cells, including cancer cells, rely on complex molecular machinery to replicate DNA as part of normal cell division.

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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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