Do no harm: a roadmap for responsible machine learning for health care

Interest in machine-learning applications within medicine has been growing, but few studies have progressed to deployment in patient care. We present a framework, context and ultimately guidelines for accelerating the translation of machine-learning-based interventions in health care. To be successful, translation will require a team of engaged stakeholders and a systematic process from beginning (problem

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A deluge of data: A pledge to the democratization of healthcare

AI and machine learning can transform data from health records — “real world data” — into “real world evidence” that will bolster the medical community’s collective knowledge exponentially. Yet, clinical decision support platforms are the only way all this added practice-based knowledge can actually be used to improve overall care. Since Stanford Medicine’s 2018 Health Trends

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Researchers turn plastic water bottles into prosthetic limbs

Artificial limbs made out of plastic water bottles could save healthcare providers millions of pounds and help tackle pollution at the same time. An expert at De Montfort University Leicester (DMU) has successfully manufactured the first-of-its-kind prosthetic limb socket made from recycled plastic bottles. Dr K Kandan, senior lecturer in Mechanical Engineering at DMU, found he could

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Heart-on-a-Chip mimics drug response seen in Humans

The platform allows the testing of conditions that cannot be easily replicated in animals. Researchers from TARA Biosystems and GlaxoSmithKline (GSK) have published data demonstrating that TARA’s engineered heart-on-a-chip system replicated drug responses found in adult humans. The findings, published in the Journal of Toxicological Sciences, show TARA’s 3D-cardiac tissue platform can predict how human hearts will

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Virtual and augmented reality can save lives by improving surgeons’ training Justin Barad position

Source STAT Rapid advances in the development of medical devices in the 21st century are contributing to healthier lives, but bring with them a new challenge: teaching clinicians how to use these often-complicated technologies. Teaching them poorly, or failing to do it at all, can negate the potential benefits and put patients at risk of

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Artificial intelligence helps detect atrial fibrillation

Researchers in the US have developed a rapid, artificial intelligence (AI)-based test that can identify patients with an abnormal heart rhythm, even when it appears normal. This 10 second test for atrial fibrillation could be a significant improvement over current test procedures that can take weeks or even years (Lancet 10.1016/S0140-6736(19)31721-0). Atrial fibrillation is a common

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