MedAI #90: Training and Application of Language Models in Medicine | Keno Bressem скачать в хорошем качестве

MedAI #90: Training and Application of Language Models in Medicine | Keno Bressem

Title: Training and Application of Language Models in Medicine Speaker: Keno Bressem Abstract: Language Models (LMs) can significantly impact the medical field by transforming textual information into usable data and addressing the shift from general language to medical language. The unique word distribution and sensitive data handling required in medical texts present distinct challenges and opportunities. Pretrained, domain specific models, such as BERT, can performs well in tasks such as extraction of procedures and ICD codes and the generation of text embeddings for downstream applications, despite its lack of conversational ability and the need for fine-tuning. Conversational medical Large Language Models (LLMs) offer a range of benefits, including accessibility, task versatility, data privacy, and educational utility. Still, they can also face issues such as hallucinations, insufficient data, errors in the data, and narrow instructions, limiting their current applicability. LMs can also take on a notable role in structuring data, particularly in the field of radiology. GPT-4 demonstrates potential for structured reporting, by converting complex free text reports into structured formats. However, limitations exist, such as the inability to use information not present in the text, potential for incorrect data entry, and privacy concerns. Understanding these aspects can contribute to a more nuanced perspective on the potential of LMs in medicine and the considerations necessary for their successful implementation. Speaker Bio: Dr. Keno Bressem is a board-certified radiologist with six years of experience at Charité – Universitätsmedizin Berlin. His clinical expertise encompasses CT, MRI, Ultrasound, X-ray, and interventional radiology. In addition to his medical expertise, Dr. Bressem is also proficient in computer science, a skill set developed through research conducted at Charité and Harvard Medical School. His dual expertise in radiology and computer science has led to over 60 publications in the field of digital medicine. Currently, Dr. Bressem leads the international COMFORT project, an EU-funded initiative that focuses on the application of AI in the treatment of urogenital cancers, underscoring his commitment to improving patient care through advanced digital solutions. ------ The MedAI Group Exchange Sessions are a platform where we can critically examine key topics in AI and medicine, generate fresh ideas and discussion around their intersection and most importantly, learn from each other. We will be having weekly sessions where invited speakers will give a talk presenting their work followed by an interactive discussion and Q&A. Our sessions are held every Thursday from 1pm-2pm PST. To get notifications about upcoming sessions, please join our mailing list: https://mailman.stanford.edu/mailman/... For more details about MedAI, check out our website: https://medai.stanford.edu. You can follow us on Twitter @MedaiStanford Organized by members of the Rubin Lab (http://rubinlab.stanford.edu) and Machine Intelligence in Medicine and Imaging (MI-2) Lab Nandita Bhaskhar (https://www.stanford.edu/~nanbhas) Amara Tariq (  / amara-tariq-475815158  )