Health IT

From AI-based image analysis to virtual therapies: Find out how digitalisation and cutting-edge IT solutions advance the medical landscape.

Photo

Health IT

Interoperability: Insights from Down Under

With interoperability stalled, stakeholders are seeking new ways to create an interoperable ecosystem. IT specialist Jason Steen describes the state of interoperability in Australia and calls for…

Photo

Discussing benefits and flaws

AI in cardiology: a marriage made in heaven – or hell?

The role of Artificial Intelligence (AI) – one of the most divisive issues in cardiology – was debated during a session of the European Society of Cardiology annual congress. Two leading experts…

Photo

AI in public health

Inspiring women to create technology that impacts society

Some people change the narrative about technology and society. One of them is Nuria Oliver, Chief Data Scientist at Data-Pop Alliance, Chief Scientific Advisor at the Vodafone Institute, and…

Photo

Healthcare IT security

Multifactor Authentication: a strong defense, but not impenetrable

IT networks of hospitals and other healthcare institutions are currently very much in the focus of both hackers and IT security specialists. In a healthcare landscape in which both organizational and…

Photo

Biological image analysis

Machine learning accelerates super-resolution microscopy

Scientists use super-resolution microscopy to study previously undiscovered cellular worlds, revealing nanometer-scale details inside cells. This method revolutionized light microscopy and earned its…

Photo

Second stroke prevention

After a stroke, AI can calculate risk of having another

Artificial intelligence (AI) can be used to give stroke patients a personalised and more accurate risk for suffering a recurrence, according to a new study presented at the European Stroke…

Photo

Cybersecurity in hospitals

Ransomware: The race between attackers and defenders

Since 2015, the number of known ransomware attacks has not only increased substantially across many industries. Hospitals, and the healthcare industry in general, have also become favorite targets of ransomware attackers, leading to very real incidents in which patient care and patients’ lives have been put at risk.

Photo

Cyberattacks and countermeasures

Healthcare cybersecurity in the EU and US: a technical, regulatory or political issue?

The pandemic has put a spotlight on the increasing role of cyberattacks and weaknesses in healthcare. In healthcare as in other industries, cybercrime does not stop at national borders. With this…

Photo

IT security

IAM: Even biometrics can be hacked

Of all the methods used in identity and access management (IAM), biometrics is arguably the oldest: it has been around long before IAM was a “thing”. Humans are naturally optimized for…

Photo

Skin cancer identification

Dermatology & AI: The need to quantify skin tones

Although artificial intelligence (AI) tools and smartphone apps that help identify suspicious moles and potential skin cancers are starting to proliferate, dermatology informatics has far to go…

Photo

Congress

Patient-centered digitalization in modern healthcare

Patient-oriented innovations and cases of the processes digitalization are presented at the Healthcare Automation and Digitalization Congress 2021 (AUTOMA+ Healthcare Edition 2021). The Congress takes place online, at BGS Online Platform on September, 27-28, 2021, and gathers hospitals, healthcare providers, and pharmaceutical companies to network and share solutions regarding the personalized…

Photo

Risk reduction, rehabilitation

The role of AI in preventive cardiology

Artificial Intelligence and Big Data in cardiovascular risk reduction and cardiac rehabilitation are offering new opportunities for increased diagnostic accuracy and more personalised exercise prescription. Experts believe it can be harnessed to design tools to enable cardiologists to make better decisions, and have more confidence in the decision-making process. The topic was featured at ESC…

Photo

Cardiology & AI

Machine learning to predict sudden cardiac death

Could machine learning (ML) help to predict sudden cardiac death (SCD)? According to Dr Sanjiv Narayan, Professor of Medicine at Stanford University, California, many exciting studies are using ML to predict sudden death in ways not previously possible. ‘Complex data, such as MRI geometry, very large electronic health records or continuous data streams from wearables, are difficult to probe…

Photo

Early detection and treatment of illnesses

Researchers develop implantable AI system

Artificial intelligence (AI) will fundamentally change medicine and healthcare: Diagnostic patient data, e.g. from ECG, EEG or X-ray images, can be analyzed with the help of machine learning, so that diseases can be detected at a very early stage based on subtle changes. However, implanting AI within the human body is still a major technical challenge. TU Dresden scientists at the Chair of…

Photo

Increased processing power

Personalizing cancer treatment with quantum computing

Cancer patients’ medical records can often comprise up to 100 terabytes of individual — and usually very heterogeneous — data, including blood and tumor values, personal indicators, sequencing and treatment data, and much more besides. Up to now, it has been virtually impossible to use this wealth of information efficiently due to a lack of appropriate processing mechanisms. As a result,…

Photo

Clinical intelligence

Dedalus and Rx.Health partner to 'liberate' healthcare data

Healthcare software company Dedalus announced its strategic partnership in North America with Rx.Health, an AI-based digital health unification and clinical intelligence platform. The partnership will enable collaboration between Dedalus’ solution, Digital Connect for Health (DC4H) with Rx.Health’s platform that unifies and automates digital health through an EHR connected formulary and 250+…

Photo

Intensive care & AI

Machine learning model predicts ICU patients' mortality risk

A research team at Universitat Autònoma de Barcelona (UAB), in collaboration with the Hospital de Mataró, developed a new machine learning-based model that predicts the risk of mortality of intensive care unit patients according to their characteristics. The research was published in the latest edition of the journal Artificial Intelligence in Medicine, with a special mention as a…

Photo

Siemens Healthineers and Flywheel

Partnership for healthcare research collaboration

Medical data management company Flywheel announced a partnership and enterprise license agreement with Siemens Healthineers. Under the agreement, Flywheel will deliver a cloud-based research collaboration solution on the Siemens Healthineers teamplay digital health platform. Rolling out first in North America, the teamplay collaboration solution will enable Siemens Healthineers and its many…

Photo

Panic prevention

Drone helps elderly escape from burning nursing homes

A student team at Eindhoven University of Technology (TU/e) has introduced an interactive drone that guides elderly people to the exit during a fire in a nursing home, even before the fire brigade arrives. The Blue Jay Aeden is said to be the first interactive drone in the world that can transmit emotions and can fulfil an important function in saving people's lives.

Photo

Connectome analysis

Machine learning improves prediction of stroke recovery

An international team of scientists led by EPFL has developed a system that combines information from the brain’s connectome – the “wiring” between neurons – and machine learning to assess and predict the outcome of stroke victims. When blood flow to the brain is somehow reduced or restricted, a person can suffer what we know as a stroke (from “ischemic stroke” in medical jargon).…

Photo

Deep learning vs Aids

AI app could help diagnose HIV more accurately

Pioneering technology developed by University College London (UCL) and Africa Health Research Institute (AHRI) researchers could transform the ability to accurately interpret HIV test results, particularly in low- and middle-income countries. Academics from the London Centre for Nanotechnology at UCL and AHRI used deep learning (artificial intelligence/AI) algorithms to improve health workers’…

Photo

WHO global report

The six guiding principles for AI in healthcare

Artificial Intelligence (AI) holds great promise for improving the delivery of healthcare and medicine worldwide, but only if ethics and human rights are put at the heart of its design, deployment, and use, according to new WHO guidance. The report, Ethics and governance of artificial intelligence for health, is the result of 2 years of consultations held by a panel of international experts…

Photo

Preprogrammed bias?

AI and the gender gap: Data holds a legacy of discrimination

Technologies based on artificial intelligence (AI) are considered the epitome of progress. However, the data AI algorithms use to draw their conclusions is outdated. It ignores the existence of biological sex and socio-cultural gender and their effects on individual health and disease states. Thus, the ‘thinking machines’ not only reproduce discriminating bias and prejudices but also produce…

Photo

Study on devices and implants

AI could improve speech recognition in hearing aids

In noisy environments, it is difficult for hearing aid or hearing implant users to understand their conversational partner because current audio processors still have difficulty focusing on specific sound sources. In a feasibility study, researchers from the Hearing Research Laboratory at the University of Bern and the Inselspital are now suggesting that artificial intelligence (AI) could solve…

Photo

HIMSS

COVID response boosted by digital transformation

Digital transformation has been a significant factor in the way hospitals have responded to the challenges posed by the COVID-19 pandemic. However, at HIMSS21 European Health Conference, experts were also quick to point out that the approach of the ‘human resource’ to the challenges and changes was a key factor.

Photo

IoT in the clinical environment

The smart hospital: A place with ears and eyes

Andrew Gostine, MD, and CEO of Artisight, talked at the recent NVIDIA's GPU Technology Conference (GTC) about Artisight’s platform that allows hospitals to deliver improved organisational and financial performance by deploying an Internet of Things (IoT) sensor network to collect data and using artificial intelligence (AI) to analyse the gathered information in a way that is compliant with the…

Photo

„Swarm Learning“

AI with swarm intelligence to analyse medical data

Communities benefit from sharing knowledge and experience among their members. Following a similar principle - called “swarm learning” - an international research team has trained artificial intelligence algorithms to detect blood cancer, lung diseases and Covid-19 in data stored in a decentralized fashion. This approach has advantage over conventional methods since it inherently provides…

Photo

Medical Device Regulation update

Lessons learned from implementing the MDR

26 May 2021 marks the Date of Application of the European Medical Device Regulation (MDR). Replacing the Medical Devices and Active Implantable Medical Devices Directives, the Regulation is a welcome update for patient safety, transparency, and access to medical devices for Europeans. COCIR has been contributing to the development and implementation of the MDR since the very first discussions in…

Photo

Cardiology

On the way to better analysis of paediatric ECGs

Physicians are increasingly using software to automatically evaluate Holter ECG signals in adult patients, but so far, no software has been developed for children. Cardiomatics and the Medical University of Warsaw are on the way to a breakthrough in paediatric cardiology. They are developing an international tool for automatic assessment, analysis, and interpretation of electrocardiographic…

Photo

Combining common risk factors

Deep learning enables dual screening for cancer and CVD

Heart disease and cancer are the leading causes of death in the United States, and it’s increasingly understood that they share common risk factors, including tobacco use, diet, blood pressure, and obesity. Thus, a diagnostic tool that could screen for cardiovascular disease while a patient is already being screened for cancer has the potential to expedite a diagnosis, accelerate treatment, and…

539 show more articles
Subscribe to Newsletter