New AI-Based Algorithm Spots Unseen Signs of Heart Failure

New AI-Based Algorithm Spots Unseen Signs of Heart Failure

A new self-learning algorithm can detect blood pumping problems by reading electrocardiograms (also known as ECGs or EKGs) to predict whether a patient was experiencing heart failure.

The special artificial intelligence (AI)-based computer algorithm created by researchers at Mount Sinai (New York, NY, USA) was able to learn how to identify subtle changes in electrocardiograms (also known as ECGs or EKGs) to predict whether a patient was experiencing heart failure.

This study represents an exciting step forward in finding information hidden within the ECG data which can lead to better screening and treatment paradigms using a relatively simple and widely available test

Read more: https://www.hospimedica.com/health-it/articles/294790199/new-self-learning-ai-based-algorithm-reads-electrocardiograms-to-spot-unseen-signs-of-heart-failure.html

High-Energy X-Rays Show Lung Vessels Altered by COVID-19

Using high-energy X-rays emitted by a special type of particle accelerator, scientists have intricately captured the damage caused by COVID-19 to the lungs’ smallest blood vessels.

Due to this intense brilliance, researchers can view blood vessels five microns in diameter (a tenth of the diameter of a hair) in an intact human lung. A clinical CT scan only resolves blood vessels that are about 100 times larger, around 1mm in diameter.

By combining our molecular methods with the HiP-CT multiscale imaging in lungs affected by COVID-19 pneumonia they understood the impact it has on oxygen levels in our circulatory system

Read more: https://www.hospimedica.com/covid-19/articles/294790408/high-energy-x-rays-emitted-by-special-particle-accelerator-show-lung-vessels-altered-by-covid-19.html

4 Trends in Enterprise Imaging Systems

Here is a list of some of the top overarching trends in enterprise radiology systems observed over the past year:

1. Introduction of Newly Engineered Cloud-based Platforms
2. Movement to Larger Cloud Data Storage Providers
3. Increased Customization Capabilities
4. Third-party Apps are Now Being Integrated

Read about these trends in detail: https://www.itnonline.com/article/4-trends-enterprise-imaging-systems

AI in radiology is just getting started, but these 4 lessons can help practices prepare

Radiology departments are just beginning to deploy artificial intelligence tools in real-world clinical practice. But learning from these early adopters can help pave the way for others in the specialty. These 4 lessons can help practices prepare better.

1. Some groups are using AI to facilitate imaging orders
2. Artificial intelligence is creating an entirely novel kind of work for rads, who may be responsible for managing new data streams
3. Monitoring and updating processes and software to track performance.
4. Assess if the value of AI outweighs its maintenance costs.

Read more: https://www.healthimaging.com/topics/ai-emerging-technologies/radiology-ai-4-lessons-help-practices-prepare

Managing displays during the pandemic requires attention to detail

Working remotely creates challenges for hospital and private practice IT personnel, who have to make sure that monitors are correctly calibrated to operate at the optimal level. But lockdown, social distancing rules, and individual radiologist concerns make it difficult for IT professionals to personally visit every radiologist’s home to confirm that systems are set up properly.

Radiologists and imaging professionals to understand the challenges and necessities of facilitating remote radiology work.

Read more: https://www.auntminnie.com/index.aspx?sec=ser&sub=def&pag=dis&ItemID=133689

Will the shift to remote reading during COVID-19 be permanent?

The COVID-19 pandemic has significantly impacted the everyday life of radiologists, forcing many to work remotely. But they must have the right technology to do so. More than simply a computer and monitors, these remote setups are considered trusted medical devices and are the primary interface between radiologists and patient data. Therefore, medical displays and how they are managed are important concerns.

Read more: https://www.auntminnie.com/index.aspx?sec=ser&sub=def&pag=dis&ItemID=133708

Radiologists are capable of differentiating COVID-19 from other lookalikes on chest CT

Radiologists are capable of differentiating COVID-19 from other atypical pneumonia on CT, according to a new analysis published in the European Journal of Radiology.

Computed tomography emerged as a useful tool for assessing patients with the novel coronavirus last year. However, it has also raised concerns among the specialty, with chest imaging lacking the specificity of viral testing and overlapping with similar findings for other infections.

German researchers set out to explore this topic in what they believe is the first study to gauge radiologists’ performance in determining patients’ stage of COVID-19 pneumonia. Physicians appeared to excel, though they did struggle to assess the early and late stages of the disease, and skill levels did not impact the results.

Read More: https://www.radiologybusiness.com/topics/care-delivery/radiologists-differentiate-covid-19-pneumonia-chest-ct

Worldwide shortage of radiologists poses challenge to breast cancer screening services

A worldwide shortage of radiologists is the “most significant challenge” for breast cancer screening services, which are still recovering from the effects of the pandemic.

Members of the national service have warned that addressing the deficit in the radiologist workforce will be critical to keeping the service going in the next couple of years.

Read More: https://www.irishexaminer.com/news/arid-40724952.html

Team to create framework for evaluating AI-based medical imaging

Artificial intelligence (AI) is showing promise in multiple medical imaging applications. Yet rigorous evaluation of these methods is important before they are introduced into clinical practice.

A multi-institutional and multiagency team led by researchers at Washington University is outlining a framework for objective task-based evaluation of AI-based methods and outlining the key role that physicians play in these evaluations. They also are providing techniques to conduct such evaluations, particularly in positron emission tomography (PET).

A key challenge to the team is attention to the primacy of ‘trustworthy AI.’ This paper lays down a rigorous framework for evaluating AI methods in the direction of improving this trust.

Read the full article: https://source.wustl.edu/2021/10/team-to-create-framework-for-evaluating-ai-based-medical-imaging/

Medical imaging is the essence of patient care

Medical imaging technologists are frontline workers and have had to endure the same pressures as other health care workers throughout the pandemic and deserve to be included alongside their peers. Thanks to multidisciplinary work that includes various players in the continuum of care, our hospitals, community service centers, medical clinics and medical imaging laboratories have succeeded in continuing to provide high-quality care.

A recent survey by the Central African Republic of its members showed that the number one obstacle to catching up on filming waiting lists is the shortage of technicians.
About 70% of respondents indicated that lack of human resources for medical imaging was the biggest obstacle to reducing waiting times.

Read the full article:
https://www.vaughantoday.ca/medical-imaging-is-the-essence-of-patient-care/