Collaborating Authors

Health & Medicine

Artificial Intelligence, Robots and the Operating Room - IEEE Transmitter


When asked about their willingness to allow robots powered by AI technology to operate on their young children (ages eight and younger), Millennial parents in a 2018 IEEE global survey were likely to allow it, particularly in Asia: 82 percent in China and 78 percent in India said they would be "very likely". Meanwhile, 45 percent in both the U.S. and U.K. say they would be "very likely". Compared to a recent 2020 global survey, a majority of Millennial parents are 29 percent extremely or 31 percent very likely to allow robots powered by AI to conduct surgery on their child. Though parents in China are 63 percent very and 26 percent extremely likely to allow robotic surgery on their child, 41 percent of American parents say they are not likely at all to allow it.

Top 10 Robotic Innovations in 2021


The machines have long since left the confines of research labs to explore new realms. They are anticipated to continue their massive spread into pharmacies, the automobile industry, and other industries. Numerous robots are already helping to improve product quality and reduce turnaround times in the manufacturing industry. These robots are proven to be effective at simple tasks and jobs. Robots are prone to fewer mistakes, need less maintenance, and are more cost-effective.

Opioids, Pain, and the Brain: Mapping Out a Healthier Future for Women < Yale School of Medicine


This well validated "machine learning" method is designed to avoid over-fitting to any specific data set and thereby increases the likelihood their findings …

Application of artificial intelligence to the electrocardiogram


Artificial intelligence (AI) has given the electrocardiogram (ECG) and clinicians reading them super-human diagnostic abilities. Trained without hard-coded rules by finding often subclinical patterns in huge datasets, AI transforms the ECG, a ubiquitous, non-invasive cardiac test that is integrated into practice workflows, into a screening tool and predictor of cardiac and non-cardiac diseases, often in asymptomatic individuals. This review describes the mathematical background behind supervised AI algorithms, and discusses selected AI ECG cardiac screening algorithms including those for the detection of left ventricular dysfunction, episodic atrial fibrillation from a tracing recorded during normal sinus rhythm, and other structural and valvular diseases. The ability to learn from big data sets, without the need to understand the biological mechanism, has created opportunities for detecting non-cardiac diseases as COVID-19 and introduced challenges with regards to data privacy. Like all medical tests, the AI ECG must be carefully vetted and validated in real-world clinical environments.

Biden vacations at Delaware beach house after week of heavy losses

FOX News

Fox News Flash top headlines are here. Check out what's clicking on President Biden took major hits this week, from the Pentagon confirming that a "tragic mistake" led to 10 civilians in Afghanistan dying in a drone strike, to the Food and Drug Administration rejecting his vaccine booster proposal, with much of the news breaking as the president headed to the beach for vacation. "So the U.S. drone strike did NOT kill any ISIS-K but did kill 10 innocent civilians, including 7 children. The Biden administration is a sad, tragic mess and an utter embarrassment on the world stage!,"

Eleos Health raises $6M for behavioral health focused AI voice tech


This morning Eleos Health, a company that uses AI-backed voice technology to gather insights into behavioral health, scored $6 million in seed funding. The funding news coincides with the company's announcement that Dr. David Shulkin, former Secretary of the U.S. Department of Veterans Affairs, has joined the company's board. The Israeli company created a tool that uses voice AI capabilities to help mental health professionals analyze their patients. Clinicians can run the technology in the background of a mental health session. The system is then able to analyze the session based on "hundreds of data parameters" and in turn give clinicians more insights and information about the patient, and in turn help personalize care.

Bringing TrackMate in the era of machine-learning and deep-learning


TrackMate is an automated tracking software used to analyze bioimages and distributed as a Fiji plugin. Here we introduce a new version of TrackMate rewritten to improve performance and usability, and integrating several popular machine and deep learning algorithms to improve versatility. We illustrate how these new components can be used to efficiently track objects from brightfield and fluorescence microscopy images across a wide range of bio-imaging experiments. Object tracking is an essential image analysis technique used across biosciences to quantify dynamic processes. In life sciences, tracking is used for instance to track single particles, sub-cellular organelles, bacteria, cells, and whole animals.

Futuristic AI-Based Computing Devices: Physicists Simulate Artificial Brain Networks With New Quantum Materials


Like biologically based systems (left), complex emergent behaviors--which arise when separate components are merged together in a coordinated system--also result from neuromorphic networks made up of quantum-materials-based devices (right). Pandemic lockdown forces a new perspective on designs for futuristic AI-based computing devices. Isaac Newton's groundbreaking scientific productivity while isolated from the spread of bubonic plague is legendary. University of California San Diego physicists can now claim a stake in the annals of pandemic-driven science. A team of UC San Diego researchers and colleagues at Purdue University have now simulated the foundation of new types of artificial intelligence computing devices that mimic brain functions, an achievement that resulted from the COVID-19 pandemic lockdown.

Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms: Buduma, Nithin, Buduma, Nikhil: 9781492082187: Books


Nithin Buduma is one of the first machine learning engineers at, a start-up based out of Harvard and Stanford working to help healthcare companies leverage their massive datasets. Nikhil Buduma is the cofounder and chief scientist of Remedy, a San Francisco-based company that is building a new system for data-driven primary healthcare. At the age of 16, he managed a drug discovery laboratory at San Jose State University and developed novel low-cost screening methodologies for resource-constrained communities. By the age of 19, he was a two-time gold medalist at the International Biology Olympiad. He later attended MIT, where he focused on developing large-scale data systems to impact healthcare delivery, mental health, and medical research.

AI Predictions


Despite a tough year for many, US companies are accelerating plans to implement artificial intelligence (AI). Another 54% are heading there fast. And they've moved way beyond just laying the foundation. Many are reaping rewards from AI right now, in part because it proved to be a highly effective response to the challenges brought about by the COVID-19 crisis. In fact, most of the companies that have fully embraced AI already report seeing major benefits.