Tag: clinical AI
On algorithms, life, and learning
From enhancing international business logistics to freeing up more hospital beds to helping farmers, MIT Professor Dimitris Bertsimas SM ’87, PhD ’88 summarized how his work in operations research has helped drive real-world improvements, while delivering the 54th annual James R. Killian Faculty Achievement Award Lecture at MIT on Thursday, March 19.Bertsimas also described how artificial intelligence is now being used in some of his scholarly projects and as a tool in MIT Open Learning efforts, which he currently directs — another facet of a highly productive and lauded career over four decades at the Institute. The Killian Award is the highest prize MIT gives its faculty.
“I have tried to improve the human condition,” Bertsimas said, summarizing the breadth of his work and the many applications to everyday living that he has found for it. Learn more
A better method for identifying overconfident large language models
Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular method involves submitting the same prompt multiple times to see if the model generates the same answer.But this method measures self-confidence, and even the most impressive LLM might be confidently wrong. Overconfidence can mislead users about the accuracy of a prediction, which might result in devastating consequences in high-stakes settings like health care or finance.
To address this shortcoming, MIT researchers introduced a new method for measuring a different type of uncertainty that more reliably identifies confident but incorrect LLM responses. Learn more
One Survivor’s AI Breakthrough Predicts Cancer Years Ahead
AI Decoded focusses on one of the most urgent, tangible uses of artificial intelligence: health care — we speak to Dr Regina Barzilay, an MIT professor who is building machine-learning AI models to predict disease. She herself was diagnosed with breast cancer in 2014, and has used that experience and knowledge to target her research towards prevention — the AI model she and her team built, named MIRAI, is now able to detect a patient’s risk of developing breast cancer within five years. Are we on the brink of a revolution in treating cancer for everyone? Find out on AI Decoded... Joining presenter Christian Fraser is AI Decoded co-host Stephanie Hare and the BBC's AI correspondent Marc Cieslak Learn more
