Large language models in medicine
Large language models (LLMs) can respond to free-text queries without being specifically
trained in the task in question, causing excitement and concern about their use in healthcare …
trained in the task in question, causing excitement and concern about their use in healthcare …
The current and future state of AI interpretation of medical images
P Rajpurkar, MP Lungren - New England Journal of Medicine, 2023 - Mass Medical Soc
The Current and Future State of AI Interpretation of Medical Images | NEJM Skip to main content
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scGPT: toward building a foundation model for single-cell multi-omics using generative AI
Generative pretrained models have achieved remarkable success in various domains such
as language and computer vision. Specifically, the combination of large-scale diverse …
as language and computer vision. Specifically, the combination of large-scale diverse …
Towards a general-purpose foundation model for computational pathology
Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks,
requiring the objective characterization of histopathological entities from whole-slide images …
requiring the objective characterization of histopathological entities from whole-slide images …
Beavertails: Towards improved safety alignment of llm via a human-preference dataset
In this paper, we introduce the BeaverTails dataset, aimed at fostering research on safety
alignment in large language models (LLMs). This dataset uniquely separates annotations of …
alignment in large language models (LLMs). This dataset uniquely separates annotations of …
[HTML][HTML] A foundation model for generalizable disease detection from retinal images
Medical artificial intelligence (AI) offers great potential for recognizing signs of health
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …
Clip-driven universal model for organ segmentation and tumor detection
An increasing number of public datasets have shown a marked impact on automated organ
segmentation and tumor detection. However, due to the small size and partially labeled …
segmentation and tumor detection. However, due to the small size and partially labeled …
Towards generalist biomedical ai
Background Medicine is inherently multimodal, requiring the simultaneous interpretation
and integration of insights between many data modalities spanning text, imaging, genomics …
and integration of insights between many data modalities spanning text, imaging, genomics …
[HTML][HTML] A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
During the diagnostic process, clinicians leverage multimodal information, such as the chief
complaint, medical images and laboratory test results. Deep-learning models for aiding …
complaint, medical images and laboratory test results. Deep-learning models for aiding …
[HTML][HTML] Benchmarking large language models' performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard
Summary Background Large language models (LLMs) are garnering wide interest due to
their human-like and contextually relevant responses. However, LLMs' accuracy across …
their human-like and contextually relevant responses. However, LLMs' accuracy across …