Can artificial intelligence (AI) potentially transform health care for the better?
Now, rising to the challenge, an Arizona State University team of researchers has built a powerful new AI tool, called Ark+, to help doctors read chest X‑rays better and improve health care outcomes.
“Ark+ is designed to be an open, reliable and ultimately useful tool in real‑world health care systems,” said Jianming “Jimmy” Liang, an ASU professor from the College of Health Solutions, and lead author of the study recently published in Nature.
Quantum Computing Innovation In Pharma — Dr. Thomas Ehmer, Ph.D. — Merck KGaA, Darmstadt, Germany
Dr. Thomas Ehmer, Ph.D. (https://www.linkedin.com/in/tehmer/) is a seasoned technology strategist with over two decades of experience in IT innovation, business development, and R&D within the pharmaceutical industry, and co-founder of the Quantum Interest Group, at Merck KGaA Darmstadt, Germany (https://www.emdgroup.com/en).
Dr. Ehmer currently is in the Sector Data Office — AI Governance and Innovation Incubator at Merck KGaA Darmstadt, Germany, where he scouts emerging and disruptive technologies, demonstrating their potential value for R&D applications, with a focus on quantum technologies.
Throughout his career at Merck KGaA Darmstadt, Germany, Dr. Ehmer has played a pivotal role in shaping IT strategy, business process optimization, and digital transformation across the entire pharmaceutical value chain, currently focusing on transparent AI and how and where emerging technology can help patients live a better life. His expertise spans technology scouting, business analysis, and IT program leadership, having successfully driven major global projects.
Beyond his corporate career, Dr. Ehmer is an active private seed investor and has contributed to quantum computing research and applications in drug discovery, authoring publications on the potential of quantum computing and machine learning in pharmaceutical R&D (https://onlinelibrary.wiley.com/doi/10.1002/9783527840748.ch26).
The drugs, sutezolid and delpazolid, have demonstrated strong antimicrobial activity and a notably better safety profile compared to linezolid, with the potential to replace this current cornerstone in the treatment of drug-resistant TB.
The findings were published in two articles in The Lancet Infectious Diseases. Research partners in Europe included Radboud University Medical Center in the Netherlands and the German Center for Infection Research (DZIF), Munich, the Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, the Center for International Health at LMU University Hospital and Helmholtz Munich.
New research suggests that medical AI chatbots are woefully unreliable at understanding how people actually communicate their health problems.
As detailed in yet-to-be-peer-reviewed study presented last month by MIT researchers, an AI chatbot is more likely to advise a patient not to seek medical care if their messages contained typos. The errors AI is susceptible to can be as seemingly inconsequential as an extra space between words, or if the patient used slang or colorful language. And strikingly, women are disproportionately affected by this, being wrongly told not to see a doctor at a higher rate than men.
Throughout their everyday lives, humans are typically required to make a wide range of decisions, which can impact their well-being, health, social connections, and finances. Understanding the human decision-making processes is a key objective of many behavioral science studies, as this could in turn help to devise interventions aimed at encouraging people to make better choices.
Researchers at Princeton University, Boston University and other institutes used machine learning to predict the strategic decisions of humans in various games. Their paper, published in Nature Human Behavior, shows that a deep neural network trained on human decisions could predict the strategic choices of players with high levels of accuracy.
“Our main motivation is to use modern computational tools to uncover the cognitive mechanisms that drive how people behave in strategic situations,” Jian-Qiao Zhu, first author of the paper, told Phys.org.
A new large-scale study spotlights postoperative delirium as a preventable and high-impact complication which is driven by patient frailty and surgical stress—and one that can be addressed through low-cost, evidence-based interventions.
The findings, which appear in JAMA Network Open, provide a call to action for clinicians, health systems, patients, and families to prioritize brain health throughout perioperative care.
“Postoperative delirium isn’t a minor complication—it’s analogous to acute brain failure, a medical emergency that should be recognized and addressed,” said Laurent Glance, MD, a professor of Anesthesiology and Perioperative Medicine at the University of Rochester Medical Center (URMC) and senior author of the study.
