Researchers at King's College Hospital and Queen Mary University of London have shown that a new computer-based algorithm can rank drugs used to treat primary liver cancer, based on their efficacy in reducing cancer cell growth.
Researchers at Karolinska Institutet have developed an AI-based tool that improves the diagnosis of breast cancer tumours and the ability to predict the risk of recurrence. The greater diagnostic precision can lead to more personalised treatment for the large group of breast cancer patients with intermediate risk tumours. The results are published in the scientific journal Annals of Oncology.
Machine learning methods are being used to predict the health of the placenta from a 30-second MRI scan. Researchers hope the approach will offer an insight into the health of expectant mothers and unborn babies by detecting the early signs of dangerous conditions such as pre-eclampsia. Researchers from the School of Biomedical Engineering & Imaging Sciences at King’s College London (KCL)…
A computer program trained to see patterns among thousands of breast ultrasound images can aid physicians in accurately diagnosing breast cancer, a new study shows. When tested separately on 44,755 already completed ultrasound exams, the artificial intelligence (AI) tool improved radiologists’ ability to correctly identify the disease by 37 percent and reduced the number of tissue samples, or…
The FDA authorized marketing of software to assist medical professionals who examine body tissues in the detection of areas that are suspicious for cancer as an adjunct to the review of digitally-scanned slide images from prostate biopsies.
Decreasing the rate of missed lesions could translate into fewer cases of colon cancer.
A team of researchers are developing the use of an artificial intelligence (AI) algorithm with the aim of diagnosing deep vein thrombosis (DVT) more quickly and as effectively as traditional radiologist-interpreted diagnostic scans, potentially cutting down long patient waiting lists and avoiding patients unnecessarily receiving drugs to treat DVT when they don’t have it.
The role of Artificial Intelligence (AI) is one of the most divisive issues in cardiology. Two leading experts argue the pros and cons of its use, exploring its benefits and advantages to cardiac care, as well as highlighting the pitfalls and shortcomings of AI, while underlining the need for clear guidelines and regulations for its use going forward.
Roche announced the introduction of the Roche Digital Pathology Open Environment that allows software developers to easily integrate their image analysis tools for tumour tissue with Roche’s uPath enterprise software, an application for pathologist workflow. This open environment allows for the secure exchange and flow of data so that pathologists can access advanced algorithms from third…
More than 50 leading digital pathology experts have been lined up for a major conference in London in December looking at all aspects of the field. Speakers will explore latest developments, new trends, challenges, and innovation, as well as the effects of Covid-19 on pathology practice, during the 8th Digital Pathology and AI Congress on December 1 and 2. Artificial intelligence will feature…
Scientists from the Nanyang Techniogical University (NTU) Singapore, in collaboration with clinicians at Tan Tock Seng Hospital (TTSH) in Singapore, have developed a novel method that uses artificial intelligence (AI) to screen for glaucoma, a group of eye diseases that can cause vision loss and blindness through damage to the optic nerve at the back of the eye. Glaucoma is often called ‘the…
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 before becoming a clinically adoptable technology. Many challenges need to be resolved, not least of which is the need for more image data representing people of colour.
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 Organisation (ESO) Conference. Experts believe the study will help to identify the most important factors for preventing stroke recurrence and has the potential to help prevent many thousands of strokes a year…
An AI-led device to assess coronary CT angiographs has been designed to assess cardiac plaque that may lead to myocardial infarction (MI). In his presentation ‘Vascular inflammation and cardiovascular risk assessment using coronary CT angiography’ (CCTA), Charambalos Antoniades, Professor of Cardiovascular Medicine at the University of Oxford, presented the research team’s findings during…
Artificial Intelligence (AI) is providing numerous opportunities across clinical care in the field of cardiovascular imaging. While challenges remain, AI is being applied in terms of diagnosis and prognosis, defining cardiovascular imaging pathways, and image acquisition and analysis. It can also help cardiologists predict which patients may do well, or which treatments are best applied to those…
Coronary computed tomography angiography (CCTA) is a non-invasive imaging test which can be used to evaluate coronary artery stenosis and measure plaques. Current plaque analysis is time-consuming and needs expert readers in order to help assess a patient’s heart attack risk. That’s about to change.
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…
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…
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…
Scientists are using artificial intelligence (AI) and the Cambridge-1 supercomputer to synthesise artificial 3-D MRI images of human brains and create models that show disease states across various ages and genders. The Synthetic Brain Project is focused on building deep learning models which have been developed by King’s College London (KCL) and NVIDIA data scientists and engineers as part of…
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 Co-founder and Vice-president of the European Laboratory for Learning and Intelligent Systems (ELLIS). In an interview with HiE, she explains how she develops computational tools and uses artificial…
Siemens Healthineers presents its second pathway for its AI-Pathway Companion at the Healthcare Information and Management Systems Society Global Health Conference 2021 (HIMSS 21). This new pathway is focused on non-small cell lung cancer, supporting personalized and standardized decision-making along the whole treatment process.
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+…
El laboratorio de Genómica Biomédica del IRB Barcelona (Institute for Research in Biomedicine) ha desarrollado un método computacional que identifica las mutaciones causantes del cáncer para cada tipo de tumor.
The Biomedical Genomics laboratory at the Institute for Research in Biomedicine (IRB) Barcelona has developed a computational tool that identifies cancer driver mutations for each tumour type. This and other developments produced by the same lab seek to accelerate cancer research and provide tools to help oncologists choose the best treatment for each patient. The study has been published in the…
