The U.S. Food and Drug Administration authorized marketing of the GI Genius, the first device that uses artificial intelligence (AI) based on machine learning to assist clinicians in detecting lesions (such as polyps or suspected tumors) in the colon in real time during a colonoscopy. “Artificial intelligence has the potential to transform health care to better assist health care providers and…
Royal Philips and Ibex Medical Analytics announced a strategic collaboration to jointly promote their digital pathology and AI solutions to hospitals, health networks and pathology labs worldwide. The combination of Philips digital pathology solution (Philips IntelliSite Pathology Solution) and Ibex’s Galen AI-powered cancer diagnostics platform, currently in clinical use in Europe and the…
What’s in a name? In the case of Asensus Surgical, Inc., previously known as TransEnterix, Inc., the recent rebranding doubles as a mission statement for the manufacturer of surgical robotics systems: The initial ‘A’ stands for artificial intelligence and augmented surgery, reflecting the company’s emphasis on new technologies designed to enhance the operator’s cognition (‘sensus’…
Medical technology company iCAD, Inc. announced that ProFound AI for 2D Mammography might notably reduce the risk of interval breast cancer, according to a new retrospective analysis. The aim of the study was to determine if adding AI to reading mammography as a supportive tool may help in decreasing the interval cancer rate in population-based organized mammography screening programs in Germany.
Experts from Sweden, Finland and Kenya are using digital microscopy combined with Artificial Intelligence (AI) to deliver a rapid and effective cervical screening service to rural locations in Kenya. The project sees AI and digital diagnostics bridge the gap between low-resource settings and the availability of centralised AI-enhanced expertise and pathology services, located in larger cities in…
Emerging technologies can screen for cervical cancer better than Pap smears and, if widely used, could save lives both in developing nations and parts of countries, like the United States, where access to health care may be limited. In Biophysics Reviews, by AIP Publishing, scientists at Massachusetts General Hospital write advances in nanotechnology and computer learning are among the…
International genomics research led by the University of Leicester has used artificial intelligence (AI) to study an aggressive form of cancer, which could improve patient outcomes. Mesothelioma is caused by breathing asbestos particles and most commonly occurs in the linings of the lungs or abdomen. Currently, only seven per cent of people survive five years after diagnosis, with a prognosis…
Healthy and cancer cells can look similar under a microscope. One way of differentiating them is by examining the level of acidity, or pH level, inside the cells. Tapping on this distinguishing characteristic, a research team from the National University of Singapore (NUS) has developed a technique that uses artificial intelligence (AI) to determine whether a single cell is healthy or cancerous…
From swallowing pills to injecting insulin, patients frequently administer their own medication. But they don’t always get it right. Improper adherence to doctors’ orders is commonplace, accounting for thousands of deaths and billions of dollars in medical costs annually. Researchers at the Massachusetts Institute of Technology (MIT) have developed a system to reduce those numbers for some…
Moderna and IBM announced their intentions to explore technologies, including artificial intelligence, blockchain and hybrid cloud, that could help support smarter Covid-19 vaccine management. Central to the effort will be a pilot of open, standardized, technology-enabled vaccine distribution approaches aimed to improve supply chain visibility and foster near real-time tracking of vaccine…
Parkinson’s disease (PD) usually causes facial abnormalities that affect a person’s self-esteem and relationships. However, these abnormalities are difficult to analyze quantitatively with current methods. To address this issue, scientists from Okayama University, Japan, explored whether commercial AI-based facial analysis software could be useful in this context. Their results show that…
Systematic review finds that machine learning models for detecting and diagnosing Covid-19 from medical images have major flaws and biases, making them unsuitable for use in patients. However, researchers have suggested ways to remedy the problem. Researchers have found that out of the more than 300 Covid-19 machine learning models described in scientific papers in 2020, none of them is suitable…
The results of a large-scale study indicate that the introduction of an AI-powered solution by healthcare software company Radlogics into radiology workflow to analyze Chest-CT scans during the Covid-19 pandemic reduced report turnaround time by an average of 30 percent, which is equivalent to 7 minutes per case.
In the move to evidence-based medicine, healthcare budgets put more pressure on efficiency, while quality of care has to meet ever increasing standards. Agfa has chosen to direct its development of artificial intelligence (AI) solutions towards helping radiology departments meet these challenges. Agfa’s SmartXR AI upgrades for its digital radiography portfolio focus on supporting operational…
AI is revamping workflows and experts showed how radiologists can integrate it into their department to improve daily practice and healthcare at ECR. The panel also discussed the health economics side of AI to help radiologists define which products make more economic sense for their department. The session tackled automated organ segmentation, an interesting application for AI in radiology.
Smart speakers, such as Amazon Echo and Google Home, have proven adept at monitoring certain health care issues at home. For example, researchers at the University of Washington have shown that these devices can detect cardiac arrests or monitor babies breathing. But what about tracking something even smaller: the minute motion of individual heartbeats in a person sitting in front of a smart…
Researchers at TU Berlin and Charité – Universitätsmedizin Berlin as well as the University of Oslo have developed a new tissue-section analysis system for diagnosing breast cancer based on artificial intelligence (AI). Two further developments make this system unique: For the first time, morphological, molecular and histological data are integrated in a single analysis. Secondly, the system…
With a growing number of Artificial Intelligence (AI) algorithms to support medical imaging analysis, finding the best solution for specific radiology tasks is not always straightforward. Many are cloaked in secrecy and commercial sensitivity and while an algorithm may perform well in one area, evidence of performance and adaptability in another environment is not always available.
One of the leading figures in global radiology has highlighted the importance of fostering a strong eco-system to advance the safe and effective implementation of AI in medical imaging. Dr Geraldine McGinty said that to fully leverage the power of AI, all stakeholders must work together but underlined the unique responsibility physicians have to ensure patient interests are best served.
The impact of Covid-19 has been devastating; countless lives lost, millions of infections worldwide, health systems overwhelmed and economies rapidly shrinking. Screening, such as for breast or cervical cancer, is an area particularly affected, with numerous appointments delayed.
The management of biopsied breast lesions that are diagnosed as abnormal but are not definitively malignant is challenging and controversial. Treatment ranges from diligent follow-up, with imaging and subsequent biopsy, to surgical excision. Researchers at the Medical University of Vienna (Medizinische Universität Wien), Austria, have developed and validated a software algorithm designed to…
Implementation of artificial intelligence into Scotland’s national breast screening service is moving closer following an initial success with a trial project. While Scotland’s breast screening trial has delivered highs and lows, significant hurdles have been overcome in terms of approvals, governance and patient acceptance.
A new deep learning system to help radiologists improve their workflow efficiency when reading high volumes of screening mammograms is being developed at Johns Hopkins University’s Radiology Artificial Intelligence Lab (RAIL) in Baltimore, MD. DeepCAT (Deep Computer-Aided Triage) is focused on workflow prioritization.
Improving workflow is one of the major challenges that radiology departments face. The need to be more efficient, deliver timely and effective patient care, and keep an eye on costs are all factors that seem to be ever-present in the modern imaging department. With the added demands of the coronavirus pandemic as radiology departments continue to play a critical role in the fight against…
Advances offered by Big Data and Artificial Intelligence within the healthcare environment are opening up new opportunities for radiographers. Roles in systems development, and being part of the safeguarding aspect by ensuring machine-based bias does not take over patient management, may be performed by radiographers alongside other contributions as AI plays an increasing role in healthcare.…
