Mayo Clinic's AI Innovation Inspires Hope in Early Detection of Pancreatic Cancer

Estimated to become the second leading cause of cancer deaths in the U.S. by 2030, pancreatic cancer has a grim prognosis with nearly 70% of patients facing mortality within the first year of diagnosis. Unfortunately, 40% of small pancreatic cancers elude detection on CT scans until they've advanced to an incurable stage.

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AI Language Models could Help Diagnose Schizophrenia

Scientists at the UCL Institute for Neurology have developed new tools, based on AI language models, that can characterise subtle signatures in the speech of patients diagnosed with schizophrenia.

The research, published in PNAS, aims to understand how the automated analysis of language could help doctors and scientists diagnose and assess psychiatric conditions.

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The Medicine of the Future could be Artificial Life Forms

Creating artificial life is a recurring theme in both science and popular literature, where it conjures images of creeping slime creatures with malevolent intentions or super-cute designer pets. At the same time, the question arises: What role should artificial life play in our environment here on Earth, where all life forms are created by nature and have their own place and purpose?

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Computer Model Predicts Who Needs Lung Cancer Screening

A machine learning model equipped with only data on people's age, smoking duration and the number of cigarettes smoked per day can predict lung cancer risk and identify who needs lung cancer screening, according to a new study publishing October 3rd in the open access journal PLOS Medicine by Thomas Callender of University College London, UK, and colleagues.

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PARMESAN: An AI-Based Predictive Tool to Find New Treatments for Genetic Disorders

To discover new treatments for genetic disorders, scientists need a thorough knowledge of prior literature to determine the best gene/protein targets and the most promising drugs to test. However, biomedical literature is growing at an explosive rate and often contains conflicting information, making it increasingly time-consuming for researchers to conduct a complete and thorough review.

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New Robot could Help Diagnose Breast Cancer Early

A device has been created that could carry out Clinical Breast Examinations (CBE).

The manipulator, designed by a team at the University of Bristol and based at the Bristol Robotics Laboratory, is able to apply very specific forces over a range similar to forces used by human examiners and can detect lumps using sensor technology at larger depths than before.

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Open Call: DigiHealthDay-2023 @ DIT-ECRI

The Premier Digital Health Event of 2023 is about to unfold. Mark your calendars for November 9th and 10th as the fourth edition of the DigiHealthDay unveils. This prominent event is hosted by the Deggendorf Institute of Technology - European Campus Rottal-Inn (DIT-ECRI) in collaboration with their dedicated PARTNERS and SPONSORS.

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AI and ChatGPT in Science and the Humanities - DFG Formulates Guidelines for Dealing with Generative Models

The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) has formulated initial guidelines for dealing with generative models for text and image creation. A statement now published by the Executive Committee of the largest research funding organisation and central self-governing organisation for science and the humanities in Germany sheds light on the influence of ChatGPT and other generative AI models on science and the humanities and on the DFG's funding activities.

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Radiologists Outperformed AI in Identifying Lung Diseases on Chest X-Ray

In a study of more than 2,000 chest X-rays, radiologists outperformed AI in accurately identifying the presence and absence of three common lung diseases, according to a study published in Radiology, a journal of the Radiological Society of North America (RSNA).

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Bayer to Collaborate with Hologic in Breast Cancer Imaging

Bayer and Hologic, Inc., today announced an international partnership to deliver contrast-enhanced-mammography (CEM) solutions to improve the detection of breast cancer in multiple countries across Canada, the European and Asia Pacific regions.

CEM is an innovative highly sensitive and low-cost breast imaging modality which combines digital mammography with the administration of a contrast agent to support breast cancer diagnosis and guide treatment decisions.

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