Search Tag: machine learning
Faster-diagnosis-of-eye-diseases-with-ai-machine-learning
2018 22 Feb
A new computational tool that uses artificial intelligence (AI) and machine learning (ML) can be used to screen patients with common retinal diseases such as macular degeneration and diabetic macular oedema. The researchers, from Shiley Eye Institute at UC San Diego Health and University of California San Diego School of Medicine, with colleagues in...Read more
Machine-learning-unpicks-the-lexical-complexity-of-radiology-reports
2018 22 Feb
In a recent study conducted at the Icahn School of Medicine at Mount Sinai in New York, researchers used machine learning (ML) techniques to identify clinical concepts in radiologist reports for CT scans (Zech et al. 2018). These techniques include natural language processing algorithms and demonstrate an important first step in the...Read more
Ai-and-ml-applications-in-healthcare
2018 20 Feb
From the algorithm development sandbox to the clinical wilderness. Today, far too many articles and blog posts suggest that artificial intelligence (AI) and machine learning (ML) is some sort of magic pill that can easily be taken to ensure that all and any problems within healthcare will disappear overnight. However, change is difficult and often...Read more
Machine-learning-detecting-early-brain-tumour-presence-1
2018 25 Jan
M a c hi ne l ea r n i n g a l g o r i t h m s i n br a i n t u mo u r i d e n t i f i c a t i o n. H o w machine learning is being utilised to cha r ac t erise agg r essive gliomas in a scalabl e analysis...Read more
Utility-of-artificial-intelligence-in-cardiology-1
2018 25 Jan
A step forward for daily practice. Artificial Intelligence (AI) tools are proving their utility in the evolving field of cardiology. However, it's necessary that cardiologists understand their full potential in order to use them efficiently in the near future. Decision making in medicine Nowadays, the decision-making process in medicine is a...Read more
Ai-tools-where-to-begin
2017 17 Oct
Amidst growing popularity of artificial intelligence-based technology in healthcare, two experts share insights that are valuable particularly for hospitals planning to purchase AI tools. Their advice: Know that AI and machine learning are augmentative tools, understand that size matters among data sets, real-world applicability is a must, and the...Read more
Machine-learning-detecting-early-brain-tumour-presence
2017 10 Oct
By tapping the power of supercomputers, combined with machine learning algorithms, a team led by University of Texas at Austin researchers have developed a method to automatically identify brain tumours. This novel method, the product of nearly a decade of research, can characterise gliomas, the most common and aggressive type of primary brain tumour....Read more
New-report-from-sectra-shows-where-radiologists-see-the-added-value-of-machine-learning
2017 09 Oct
A new report from medical imaging IT and cybersecurity company Sectra shows in what areas of the diagnostic process radiologists themselves see the added value of machine learning. The report clearly shows more opportunities than threats. Artificial Intelligence (AI) and machine learning are set to disrupt the practice of radiology. How and...Read more
Enabling-machine-learning-in-critical-care
2017 15 Sep
Critical care units are home to some of the most sophisticated patient technology within hospitals. In parallel, the field of machine learning is advancing rapidly and increasingly touching our lives. To facilitate the adoption of machine learning approaches in critical care, we must become better at sharing and integrating data. Greater emphasis on...Read more
Ai-and-the-patient
2017 05 Sep
Artificial intelligence technology is evolving quickly. An increasing number of hospitals now use AI and machine learning for more efficient care management. With powerful analytics tools, providers can gauge capacity or pinpoint the slack in the system. In addition, AI-based virtual assistants are helping more patients to stay fit and healthy....Read more
Which-2-pieces-of-health-technology-are-essential-for-the-ciso-s-arsenal
2017 22 Aug
Artificial intelligence means using computers and tools to do something that humans do. Machine learning is a subset of overall AI that recognises patterns in data and predicts outcomes based on past experience and data. Most AI systems incorporate machine learning technology to help generate results that replicate human ones. You might also like...Read more
Machine-learning-for-costly-illnesses
2017 06 Jun
Machine learning algorithms now enable some hospitals in Boston to predict diabetes and heart disease hospitalisations up to a year in advance with 82% accuracy. In contrast, guidelines used by cardiologists to predict a patient’s risk of cardiovascular disease are about 56% accurate. Indeed, those algorithms could become even more accurate with the...Read more
Ats-2017-machine-learning-may-help-to-identify-sepsis-early
2017 24 May
Using electronic health records (EHRs) to identify patients in hospital at risk for sepsis is now possible using machine learning. Machine learning does not rely on rules, but is able to learn complex patterns in data without being programmed to do so. Researchers from the University of Pennsylvania Health System presented their study of a machine-learning...Read more
Taking-the-mystery-out-of-machine-learning
2017 06 Apr
Radiologists have been taught to fear machine learning. It means what it says, a machine can learn. It is an inherently frightening concept. It is almost a shame to put such a label on the process, because it is not really new. Remember Fuzzy Logic? Neural Networks? We were all impressed that a computer could recognize the letter “A”, but that...Read more
Taking-the-mystery-out-of-machine-learning
2017 06 Apr
Radiologists have been taught to fear machine learning. It means what it says, a machine can learn. It is an inherently frightening concept. It is almost a shame to put such a label on the process, because it is not really new. Remember Fuzzy Logic? Neural Networks? We were all impressed that a computer could recognize the letter “A”, but that...Read more
Terarecon-demonstrates-deep-learning-workflow-at-himss17
2017 21 Feb
Prototype WIA Cloud engines learn from physician-driven workflow and improve automation in real-time TeraRecon , a leader in advanced visualization and enterprise medical image viewing solutions, is demonstrating their Within Image Analysis (WIA™) Cloud* machine learning solution this week at Healthcare Information & Management Systems Society (HIMSS17)...Read more
2017-digital-health-summit-ces-2017
2017 05 Jan
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Internet-of-things-north-america-2017
2017 29 Mar
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Hospital-readmissions-and-machine-learning
2016 01 Jul
The need to improve the efficiency of the healthcare services has emerged over recent decades and, especially, during the last few years with the economic and financial crisis, developed countries have been suffering The ageing population, the sector most affected by chronic diseases, is seeking better results when they need the healthcare services...Read more
Human-plus-ai-imaging-analysis-boosts-cancer-diagnosis-to-99-5-1
2016 21 Jun
A combination of the decades-long practice of diagnosing illnesses by manually reviewing images under a microscope and artificial intelligence (AI), can help doctors improve accuracy of breast and other cancer diagnosis to a rate of 99.5 percent. A research team from Beth Israel Deaconess Medical Center (BIDMC) in Boston and Harvard Medical...Read more
Computers-learning-to-improve-clinical-trial-participation
2016 28 Apr
With medical research struggling to recruit necessary numbers for clinical trials and studies being compromised or halted altogether, scientists are teaching computers to figure out why people accept or decline invitations to take part. Researchers at Cincinnati Children's Hospital Medical Centre have reported in the Journal of the American...Read more
Xerox-system-helps-hospitals-better-predict-readmissions
2015 28 Jan
Midas+, a subsidiary of Connecticut-based Xerox, is combining its vast data resources with five years of Medicare and claims data to help hospitals better predict readmissions. With this new system, known as Midas+ Readmission Penalty Forecaster, a hospital can get a much more accurate prediction or “near real-time” information on both patient patterns...Read more