Search Tag: machine learning
2020 15 Jan
Subject Index for Volume 19, issues 1-4, 2019. Issue Pages Link Issue 1 1-64 https://iii.hm/10cv Issue 2 65-128 https://iii.hm/10cw Issue 3 129-192 https://iii.hm/10cx Issue 4 193-256 https://iii.hm/10cy Acute Respiratory Distress Syndrome Use of sedation...Read more
2019 21 Nov
This year’s Scientific Assembly and Annual Meeting, the Radiological Society of North America (RSNA) will feature a newly expanded Artificial Intelligence (AI) Hub as the technology becomes increasingly embedded in imaging processes. You might also like: RSNA 2019: Speakers and Topics AI innovations from industry leaders, AI...Read more
2019 13 Nov
Summary: Where do the computer sciences have the potential to reduce radiologist burnout, reduce costs and make workflow more efficient and what are the first steps in implementing the technology? In the long-term future, I think that computers will take over the work of image interpretation from humans, just as computers...Read more
2019 11 Nov
3D printing applications in radiology – an early adopter of this technology – are poised to grow rapidly with availability of new, more flexible materials and pioneering machine learning techniques. The advancement in the nature of materials available can be considered as one of the biggest developments in 3D printing, according to experts...Read more
2019 11 Nov
Technology continues to transform healthcare through increased efficiency in work processes, leading to better delivery of care. For the incoming year, 2020, expect growing applications of artificial intelligence and machine learning aimed at advancing disease risk prediction. Expanding AI use will likely have a ripple effect, such as in genomic...Read more
2019 21 Oct
Sepsis is a major cause of death among hospitalised patients. It affects nearly 6% of all admissions and results in in-hospital mortality of greater than 15%. Early detection could reduce mortality, as it would result in the timely implementation of evidence-based interventions. Clinical researchers have developed and implemented a machine-learning...Read more
2019 20 Sep
Heart failure is a common complication in patients suffering from Type 2 Diabetes (T2D). Recently, new medicines have been developed to offset these risks; however, finding effective strategies to identify which T2D patients are most at risk has been difficult. Researchers at Brigham and Women’s Hospital and UT Southwestern Medical Centre have...Read more
2019 10 Sep
Physicians' expertise is founded on medical science and many of them may not have much familiarity with artificial intelligence (AI) techniques, now fast becoming "de rigueur" in medical practice. But, thanks to automated deep learning, even clinicians that aren’t experts in AI may be able to create AI algorithms that can help them with early detection...Read more
2019 26 Aug
Summary: Combine the characteristic of our engagement with social media with existing technology and how we could improve patient compliance in the not so distant future. Patient treatment compliance is a significant barrier and a challenge for healthcare professionals the world over. While several studies have been conducted leading to...Read more
2019 26 Aug
Summary: How a European Society of Radiology flagship initiative is addressing quality and safety in medical imaging. EUROSAFE IMAGING has celebrated five years of success in its mission to support and strengthen medical radiation protection across Europe. Through its Stars network, EUROSAFE IMAGING makes efforts to give radiation protection...Read more
2019 26 Aug
Enhanced diagnostic accuracy of screening mammography with the use of Artificial Intelligence Breast cancer is the most frequent cancer among women, with an estimated incidence of 560,000 cases in 2018, in Europe. 1 The World Health Organisation (WHO) estimated that 627,000 women worldwide, 2 out of which 150.0002 only in Europe, died from...Read more
2019 23 Aug
Acute Kidney Injury (AKI) is a common occurrence for critically ill patients in the ICU, and its early diagnosis has proven to be challenging. The accuracy of the online, machine-learning-based prediction model, AKIpredictor , was analysed for its use in a clinical setting. The study, which took place over five ICUs in Belgium, compared the predictions...Read more
2019 07 Aug
RSNA have announced Artificial Intelligence (AI) applications will feature prominently at the 105th Scientific Assembly and Annual Meeting being held this December in Chicago. You might also like: AI and Teleradiology Impact Healthcare Sponsored by Zebra Medical Vision, the one-stop AI showcase will be located...Read more
2019 07 Aug
Some artificial intelligence (AI)-based techniques are helping improve prediction of risks for certain diseases or disorders. Machine-learning models, for example, can be trained to find patterns ("features") in patient data and then determine a patient's risk of having lung cancer. You might also like: Machine Learning to Recognise Cardiac...Read more
2019 05 Jun
Over 40 million mammography exams are conducted in the United States every year, with the volume of images growing exponentially. Radiologists workloads further increase with the implementation of innovative screening technologies like digital breast tomosynthesis (DBT) that require more reading and testing time, increasing the pressure to deliver...Read more
2019 29 May
Nearly 600,000 people in the US and Europe combined sustain an out-of-hospital cardiac arrest (OHCA) annually. OHCA is a life-threatening condition, and in order to improve survival rates, it is imperative that it is recognised rapidly by medical dispatchers. Accurate recognition of OHCA either by a bystander or a dispatcher is essential for initiation...Read more
2019 21 May
Google and Northwestern scientists show precision of new deep learning system to predict lung cancer An artificial intelligence system, using deep learning, successfully detected malignant lung nodules on low-dose chest computed tomography (LDCT) scans, performing equal to, or better than expert radiologists, according to a new study from...Read more
2019 14 May
Artificial intelligence ( AI ) has shown promise to select heart failure patients for expensive treatments to prevent lethal arrhythmias , reports a study presented at ICNC 2019. The study is the first to use a machine learning algorithm to predict sudden death in heart failure patients . The International Conference on Nuclear Cardiology and...Read more
2019 07 May
Identifying women at risk for breast cancer is a critical component of effective early disease detection . Available models that use factors such as family history and genetics are inadequate in predicting an individual woman's likelihood of being diagnosed with the disease. Researchers from two major institutions have developed a new...Read more
2019 07 May
Johns Hopkins Medicine researchers develop an image-based computer model of tumour behavior that captures more of the complexity of cancer growth Researchers at Johns Hopkins Medicine have created a similar approach to the one used by the navigation application "Google Maps" to help more accurately compute and visualise the structural and...Read more
2019 12 Apr
Students attending a computer science seminar at the Technical University of Munich (TUM) recently embarked on an interesting scientific mission: predicting which character in the Game of Thrones would have the best chance to sit on the Iron Throne! In order to do this, these students developed an application that scours the web for data related...Read more
2019 10 Apr
A new study shows that incorporating modern deep machine learning networks into prognostic models is feasible in congenital heart disease. The researchers used data from over 10 000 patients and 44,000 medical reports available at a tertiary centre for congenital heart disease and pulmonary hypertension and combined this information with demographic,...Read more
2019 26 Mar
Automating symptoms recording clerical aspects of medical record keeping through speech recognition during a patient’s visit 1 could allow physicians to dedicate more time directly with patients, according to a new report published in JAMA Intern Med . Researchers considered the feasibility of using machine learning to automatically populate...Read more
2019 20 Mar
At this years 39th International Symposium on Intensive Care and Emergency Medicine , Professor Jerry Nolan , a consultant in anaesthesia and intensive care medicine at the Royal United Hospital, Bath, talked about new developments in CPR during the Max Harry Weil Lecture, one of the most important presentations at #ISICEM19. Dr. Max Harry Weil...Read more
2019 06 Mar
EuroSafe Imaging celebrated 5 years of success in it’s mission to support and strengthen medical radiation protection across Europe following a holistic, inclusive approach with a dedicated series of sessions, activities and events during this year’s European Congress of Radiology . The flagship initiative created by the European Society of...Read more
2019 06 Mar
Incoming European Society of Radiology president Boris Brkljačić 's announces his vision for ECR2020. True to tradition, on the last day of the ECR2019, incoming ESR President Boris Brkljačić, professor of radiology and vice-dean at University of Zagreb School of Medicine, Zagreb, Croatia, and chair of the Department of Diagnostic and Interventional...Read more
2019 06 Mar
Amazon Web Services (AWS) is supporting machine learning in patient care at Beth Israel Deaconess Medical Center (BIDMC) with an academic research grant. With a range of AWS machine learning services, the Harvard Medical School -affiliated teaching hospital will explore new ways that the technology can enhance clinical care,...Read more
2019 06 Mar
Professor Luis Donoso-Bach , head of the department of medical imaging, Hospital Clinic of Barcelona, presented the keynote lecture “ Artificial Intelligence and Machine Learning Informatics: management and performance analysis.” It his poignant and informative presentation he emphasised “ the race is on” as the roles in the healthcare continuum...Read more