Healthcare AI – 2023 Health IT Predictions

As we head into 2023, we wanted to kick off the new year with a series of 2023 Health IT predictions.  We asked the Healthcare IT Today community to submit their predictions and we received a wide ranging set of responses that we grouped into a number of themes.  Check out our communities predictions below and be sure to add your own thoughts and/or places you disagree with these predictions in the comments and on social media. Check out our community’s healthcare AI predictions. Evangelos Hytopoulos, Sr. Director of Data Science at iRhythm Technologies There is no doubt that AI has become mainstream in many areas. In medicine, AI approaches are currently both developed and deployed at a rapid rate, fueled by the dearth of data that already exist from different modalities (genetic, genomic, images, EHR, etc.), as well as the continuous streams of data that are provided by wearables. The majority of models today are based on supervised learning, where labels are combined with measurements to teach an algorithm to predict unseen data. However, it takes a lot of effort to create a labeled data set and as a result, usually only a subset of the data can be labeled – thus limiting the learning capacity of the current models. In upcoming years, we can expect to see AI approaches that are based on the use of self-supervised and generative AI algorithms in order to facilitate the incorporation of a larger volume of data in model training. Supervised learning is capable of le...
Source: EMR and HIPAA - Category: Information Technology Authors: Tags: AI/Machine Learning Health IT Company Healthcare IT 2023 Health IT Predictions 4D Path Carlene MacMillan CommBox Dave Bennett Evangelos Hytopoulos Gabriel Mecklenburg Healthcare AI Hinge Health iRhythm Technologies Judy Jiao Na Source Type: blogs