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Mashup Score: 13
The relentless increase in administrative responsibilities, amplified by electronic health record (EHR) systems, has diverted clinician attention from direct patient care, fuelling burnout.1 In response, large language models (LLMs) are being adopted to streamline clinical and administrative tasks. Notably, Epic is currently leveraging OpenAI’s ChatGPT models, including GPT-4, for electronic messaging via online portals.2 The volume of patient portal messaging has escalated in the past 5–10 years,3 and general-purpose LLMs are being deployed to manage this burden.
Source: www.thelancet.comCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 13
The relentless increase in administrative responsibilities, amplified by electronic health record (EHR) systems, has diverted clinician attention from direct patient care, fuelling burnout.1 In response, large language models (LLMs) are being adopted to streamline clinical and administrative tasks. Notably, Epic is currently leveraging OpenAI’s ChatGPT models, including GPT-4, for electronic messaging via online portals.2 The volume of patient portal messaging has escalated in the past 5–10 years,3 and general-purpose LLMs are being deployed to manage this burden.
Source: www.thelancet.comCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 13
The relentless increase in administrative responsibilities, amplified by electronic health record (EHR) systems, has diverted clinician attention from direct patient care, fuelling burnout.1 In response, large language models (LLMs) are being adopted to streamline clinical and administrative tasks. Notably, Epic is currently leveraging OpenAI’s ChatGPT models, including GPT-4, for electronic messaging via online portals.2 The volume of patient portal messaging has escalated in the past 5–10 years,3 and general-purpose LLMs are being deployed to manage this burden.
Source: www.thelancet.comCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 0Large language models are poor medical coders: Study - 9 day(s) ago
“New study reveals that large language models from OpenAI, Google, and Meta are not accurate medical coders, with accuracy rates below 50%. GPT-4 shows the best
Source: www.beckershospitalreview.comCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 10
With the rapid growth of interest in and use of large language models (LLMs) across various industries, we are facing some crucial and profound ethical concerns, especially in the medical field. The unique technical architecture and purported emergent abilities of LLMs differentiate them substantially from other artificial intelligence (AI) models and natural language processing techniques used, necessitating a nuanced understanding of LLM ethics. In this Viewpoint, we highlight ethical concerns stemming from the perspectives of users, developers, and regulators, notably focusing on data privacy and rights of use, data provenance, intellectual property contamination, and broad applications and plasticity of LLMs.
Source: www.thelancet.comCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 50Large language models to identify social determinants of health in electronic health records - 4 month(s) ago
npj Digital Medicine – Large language models to identify social determinants of health in electronic health records
Source: www.nature.comCategories: General Medicine News, Hem/OncsTweet
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Mashup Score: 7
Background: Artificial intelligence is increasingly being applied to many workflows. Large language models (LLMs) are publicly accessible platforms trained to understand, interact with, and…
Source: preprints.jmir.orgCategories: General Medicine News, Oncologists1Tweet
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Mashup Score: 4Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study - 5 month(s) ago
Physician’s clinical notes about an initial seizure-like event include substantial signals for prediction of seizure recurrence, and additional domain-specific and location-specific pre-training can significantly improve the performance of clinical large language models, even for specialised cohorts.
Source: www.thelancet.comCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 0
Physicians document a wealth of helpful information in their clinical notes for predicting seizure recurrence following a first unprovoked seizure in children. This is the one of the take-home messages of the retrospective cohort study by Brett Beaulieu-Jones and colleagues in The Lancet Digital Health.1
Source: www.thelancet.comCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 4Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study - 5 month(s) ago
Physician’s clinical notes about an initial seizure-like event include substantial signals for prediction of seizure recurrence, and additional domain-specific and location-specific pre-training can significantly improve the performance of clinical large language models, even for specialised cohorts.
Source: www.thelancet.comCategories: General Medicine News, Future of MedicineTweet
NEW Comment from @dbittermanmd and colleagues: The effect of using a large language model to respond to patient messages. #LLMs Read it here: https://t.co/0r4rQMxYNx https://t.co/hYCLsOuggj