Large Language Models (LLMs) have emerged as powerful candidates to inform clinical decision-making processes. While these models play an increasingly prominent role in shaping the digital landscape, two growing concerns emerge in healthcare applications: 1) to what extent do LLMs exhibit social bias based on patients' protected attributes (like race), and 2) how do design choices (like architecture design and prompting strategies) influence the observed biases? To answer these questions rigorously, we evaluated eight popular LLMs across three question-answering (QA) datasets using clinical vignettes (patient descriptions) standardized for bias evaluations. We employ red-teaming strategies to analyze how demographics affect LLM outputs, comparing both general-purpose and clinically-trained models. Our extensive experiments reveal various disparities (some significant) across protected groups. We also observe several counter-intuitive patterns such as larger models not being necessarily less biased and fined-tuned models on medical data not being necessarily better than the general-purpose models. Furthermore, our study demonstrates the impact of prompt design on bias patterns and shows that specific phrasing can influence bias patterns and reflection-type approaches (like Chain of Thought) can reduce biased outcomes effectively. Consistent with prior studies, we call on additional evaluations, scrutiny, and enhancement of LLMs used in clinical decision support applications.

The link between chronic pain and a loss of appetite may finally be understood – in mice at least. Zhi Zhang at the University of Science and Technology of China in Hefei and his colleagues injected mice with bacteria that provoke chronic pain. Ten days later, these mice were eating less frequently and for shorter periods of time compared with control mice that had been injected with saline. When the first group of mice were later given pain medication, they ate normally, the researchers wrote in a paper published in Nature Metabolism. To better understand the neuronal activity responsible for this change in behaviour, the researchers analysed the brains of the first group of mice while the animals were in chronic pain.

Ever since Corey Walker, MD, became a spine surgeon, the traditional measure of success focused on how well a patient was able to walk, bend or move after spine surgery. Now, with the help of artificial intelligence, Walker is measuring success differently. "The unique thing we're doing with this project is really focusing in on the pain medication part of it, because opioid addiction continues to be a challenge, and we are looking for ways to improve pain management after surgery," Walker said. Walker's team, in collaboration with the Cedars-Sinai Department of Computational Biomedicine, is using artificial intelligence and machine learning to predict which patients are most likely to successfully manage their pain post-surgery, and which patients might need additional assistance. "This project uses artificial intelligence algorithms to analyze millions of data points and predict which patients may need additional help with pain management after surgery," said Jason Moore, PhD, chair of the Department of Computational Biomedicine and acting professor of Medicine.

It can travel more than 25,000 miles alongside customers, work more than 100,000 hours, and check up to 30,000 products an hour. It takes its time strolling through the aisles. Moving at the same speed of a small child but heavy enough that it cannot easily topple over, Tally the robot can audit stock keeping units with 97 percent accuracy. Meanwhile it would take humans a full week to do the same amount of work and results as Tally with only 65 percent accuracy. Who wouldn't want Tally, or a similar robot, in their stores?

Knee replacement surgery, also known as knee arthroplasty, can be lifestyles-altering for lots people who suffer from osteoarthritis and different knee troubles. This procedure can remove pain and repair mobility, allowing patients to renew an energetic lifestyle. Arthroplasty may either be done in conventional way, wherein the surgeon seats the implant manually, or with the help of a robot arm controlled by means of the surgeon. Standard knee replacement uses X-ray images and relies on the surgeon's visual assessment of the knee and direct manual surgery. The robotic knee procedure involves CT scanning, which allows the surgeon to build a virtual model of the patient's knee and make a preoperative plan.

What is minimally invasive surgery? Some argue that this benign-sounding concept just transfers the pain of the operation from the patient to the surgeon. Others can't even agree on a definition of the term, believing that any procedure that causes less morbidity is by nature minimally invasive. I think that the definition question at least should be left up to the patient. When the person who will have to undergo the procedure asks, "Do I have to?" it's a good bet you're talking about something invasive.

There is a widely reported threat to our economy: robots are going to replace human workers. It is nothing new… In 1930, Keynes, the famous economist introduced the term "technological unemployment"… We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come--namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour. There is a long Wikipedia article on technological unemployment, where you can learn that people have been concerned about it for centuries… long before we could even imagine robots and computers. It is a recurrent theme of western thought.