Andrew L. Beam
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View article: NeoCLIP: a self-supervised foundation model for the interpretation of neonatal radiographs
NeoCLIP: a self-supervised foundation model for the interpretation of neonatal radiographs Open
View article: TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translation
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translation Open
View article: The need for guardrails with large language models in pharmacovigilance and other medical safety critical settings
The need for guardrails with large language models in pharmacovigilance and other medical safety critical settings Open
Large language models (LLMs) are useful tools with the capacity for performing specific types of knowledge work at an effective scale. However, LLM deployments in high-risk and safety-critical domains pose unique challenges, notably the is…
View article: Development and validation of a deep learning model for diagnosing neuropathic corneal pain via in vivo confocal microscopy
Development and validation of a deep learning model for diagnosing neuropathic corneal pain via in vivo confocal microscopy Open
View article: PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods Open
The Prediction model Risk Of Bias ASsessment Tool (PROBAST) is used to assess the quality, risk of bias, and applicability of prediction models or algorithms and of prediction model/algorithm studies. Since PROBAST’s introduction in 2019, …
View article: Doubly Robust Monte Carlo Tree Search
Doubly Robust Monte Carlo Tree Search Open
We present Doubly Robust Monte Carlo Tree Search (DR-MCTS), a novel algorithm that integrates Doubly Robust (DR) off-policy estimation into Monte Carlo Tree Search (MCTS) to enhance sample efficiency and decision quality in complex environ…
View article: Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era
Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era Open
Although prediction models for heart transplantation outcomes have been developed previously, a comprehensive benchmarking of survival machine learning methods for mortality prognosis in the most contemporary era of heart transplants follo…
View article: Improved Generalizability in Medical Computer Vision: Hyperbolic Deep Learning in Multi-Modality Neuroimaging
Improved Generalizability in Medical Computer Vision: Hyperbolic Deep Learning in Multi-Modality Neuroimaging Open
Deep learning has shown significant value in automating radiological diagnostics but can be limited by a lack of generalizability to external datasets. Leveraging the geometric principles of non-Euclidean space, certain geometric deep lear…
View article: NeoCLIP: A Self-Supervised Foundation Model for the Interpretation of Neonatal Radiographs
NeoCLIP: A Self-Supervised Foundation Model for the Interpretation of Neonatal Radiographs Open
Importance Artificial intelligence (AI) based on deep learning has shown promise in adult and pediatric populations in the interpretation of medical imaging to make important diagnostic and management recommendations. However, there has be…
View article: Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Data
Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Data Open
The g-formula can be used to estimate causal effects of sustained treatment strategies using observational data under the identifying assumptions of consistency, positivity, and exchangeability. The non-iterative conditional expectation (N…
View article: DAG-aware Transformer for Causal Effect Estimation
DAG-aware Transformer for Causal Effect Estimation Open
Causal inference is a critical task across fields such as healthcare, economics, and the social sciences. While recent advances in machine learning, especially those based on the deep-learning architectures, have shown potential in estimat…
View article: Author Correction: Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines
Author Correction: Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines Open
View article: The diagnostic and triage accuracy of the GPT-3 artificial intelligence model: an observational study
The diagnostic and triage accuracy of the GPT-3 artificial intelligence model: an observational study Open
The National Heart, Lung, and Blood Institute.
View article: The Need for Guardrails with Large Language Models in Medical Safety-Critical Settings: An Artificial Intelligence Application in the Pharmacovigilance Ecosystem
The Need for Guardrails with Large Language Models in Medical Safety-Critical Settings: An Artificial Intelligence Application in the Pharmacovigilance Ecosystem Open
Large language models (LLMs) are useful tools with the capacity for performing specific types of knowledge work at an effective scale. However, LLM deployments in high-risk and safety-critical domains pose unique challenges, notably the is…
View article: TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods Open
The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting recommendations for studies developing or evaluating the performa…
View article: Statin Twitter: Human and Automated Bot Contributions, 2010 to 2022
Statin Twitter: Human and Automated Bot Contributions, 2010 to 2022 Open
Background Many individuals eligible for statin therapy decline treatment, often due to fear of adverse effects. Misinformation about statins is common and drives statin reluctance, but its prevalence on social media platforms, such as Twi…
View article: Assessment of the clinical knowledge of ChatGPT-4 in neonatal-perinatal medicine: a comparative analysis with ChatGPT-3.5
Assessment of the clinical knowledge of ChatGPT-4 in neonatal-perinatal medicine: a comparative analysis with ChatGPT-3.5 Open
View article: Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines
Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines Open
The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have be…
View article: Large Language Models in Mental Health Care: a Scoping Review
Large Language Models in Mental Health Care: a Scoping Review Open
Objectieve:This review aims to deliver a comprehensive analysis of Large Language Models (LLMs) utilization in mental health care, evaluating their effectiveness, identifying challenges, and exploring their potential for future application…
View article: Safe and reliable transport of prediction models to new healthcare settings without the need to collect new labeled data
Safe and reliable transport of prediction models to new healthcare settings without the need to collect new labeled data Open
How can practitioners and clinicians know if a prediction model trained at a different institution can be safely used on their patient population? There is a large body of evidence showing that small changes in the distribution of the cova…
View article: Why We Support and Encourage the Use of Large Language Models in <i>NEJM AI</i> Submissions
Why We Support and Encourage the Use of Large Language Models in <i>NEJM AI</i> Submissions Open
Large language models (LLMs) promise to revolutionize many aspects of the creation and dissemination of scientific knowledge; however, their use in scientific writing remains controversial, because of concerns about authorship, originality…
View article: Labrador: Exploring the Limits of Masked Language Modeling for Laboratory Data
Labrador: Exploring the Limits of Masked Language Modeling for Laboratory Data Open
In this work we introduce Labrador, a pre-trained Transformer model for laboratory data. Labrador and BERT were pre-trained on a corpus of 100 million lab test results from electronic health records (EHRs) and evaluated on various downstre…
View article: Illuminating protein space with a programmable generative model
Illuminating protein space with a programmable generative model Open
Three billion years of evolution has produced a tremendous diversity of protein molecules 1 , but the full potential of proteins is likely to be much greater. Accessing this potential has been challenging for both computation and experimen…
View article: Performance of a Large Language Model on Practice Questions for the Neonatal Board Examination
Performance of a Large Language Model on Practice Questions for the Neonatal Board Examination Open
This Diagnostic/Prognostic Study evaluates the performance of a large language model in generating answers to practice questions for the neonatal-perinatal board examination.
View article: Survival Machine Learning Methods for Mortality Prediction After Heart Transplantation
Survival Machine Learning Methods for Mortality Prediction After Heart Transplantation Open
Although prognostic models for heart transplantation (HTx) have been developed, a comprehensive benchmarking of survival machine learning methods for mortality prognosis has not been performed. Futhermore, assessing mortality in the most c…
View article: Conformal Prediction with Large Language Models for Multi-Choice Question Answering
Conformal Prediction with Large Language Models for Multi-Choice Question Answering Open
As large language models continue to be widely developed, robust uncertainty quantification techniques will become crucial for their safe deployment in high-stakes scenarios. In this work, we explore how conformal prediction can be used to…
View article: Assessment of ChatGPT success with specialty medical knowledge using anaesthesiology board examination practice questions
Assessment of ChatGPT success with specialty medical knowledge using anaesthesiology board examination practice questions Open
View article: Artificial Intelligence in Medicine
Artificial Intelligence in Medicine Open
View article: Correction to: Artificial Intelligence Based on Machine Learning in Pharmacovigilance: A Scoping Review
Correction to: Artificial Intelligence Based on Machine Learning in Pharmacovigilance: A Scoping Review Open
View article: The Diagnostic and Triage Accuracy of the GPT-3 Artificial Intelligence Model
The Diagnostic and Triage Accuracy of the GPT-3 Artificial Intelligence Model Open
Importance Artificial intelligence (AI) applications in health care have been effective in many areas of medicine, but they are often trained for a single task using labeled data, making deployment and generalizability challenging. Whether…