Machine learning in rare disease
High-throughput profiling methods (such as genomics or imaging) have accelerated basic
research and made deep molecular characterization of patient samples routine. These …
research and made deep molecular characterization of patient samples routine. These …
[HTML][HTML] A multifaceted benchmarking of synthetic electronic health record generation models
Synthetic health data have the potential to mitigate privacy concerns in supporting
biomedical research and healthcare applications. Modern approaches for data generation …
biomedical research and healthcare applications. Modern approaches for data generation …
Technology platforms and approaches for building and evaluating machine learning methods in Healthcare
SD Mooney - The journal of applied laboratory medicine, 2023 - academic.oup.com
Background Artificial intelligence (AI) methods are becoming increasingly commonly
implemented in healthcare as decision support, business intelligence tools, or, in some …
implemented in healthcare as decision support, business intelligence tools, or, in some …
[HTML][HTML] Machine learning methods to predict 30-day hospital readmission outcome among US adults with pneumonia: analysis of the national readmission database
Background Hospital readmissions for pneumonia are a growing concern in the US, with
significant consequences for costs and quality of care. This study developed the rule-based …
significant consequences for costs and quality of care. This study developed the rule-based …
[HTML][HTML] Fib-4 score is able to predict intra-hospital mortality in 4 different SARS-COV2 waves
Increased values of the FIB-4 index appear to be associated with poor clinical outcomes in
COVID-19 patients. This study aimed to develop and validate predictive mortality models …
COVID-19 patients. This study aimed to develop and validate predictive mortality models …
Public Health Informatics and the Perioperative Physician: Looking to the Future
SC Mudumbai, RA Gabriel, S Howell… - Anesthesia & …, 2024 - journals.lww.com
The role of informatics in public health has increased over the past few decades, and the
coronavirus disease 2019 (COVID-19) pandemic has underscored the critical importance of …
coronavirus disease 2019 (COVID-19) pandemic has underscored the critical importance of …
[HTML][HTML] RApid Throughput Screening for Asymptomatic COVID-19 Infection With an Electrocardiogram: A Prospective Observational Study
D Adedinsewo, J Dugan, PW Johnson… - Mayo Clinic …, 2023 - Elsevier
Objective To evaluate the ability of a neural network to identify severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) infection using point-of-care electrocardiography …
syndrome coronavirus 2 (SARS-CoV-2) infection using point-of-care electrocardiography …
[图书][B] A Model-to-data Approach for Building Accurate Machine Learning Algorithms on EHR Data
Y Yan - 2022 - search.proquest.com
Over the past few decades, information about patients' diagnoses, medication, and
procedures has been collected and transformed into standardized and shareable electronic …
procedures has been collected and transformed into standardized and shareable electronic …
The NLP Sandbox: an efficient model-to-data system to enable federated and unbiased evaluation of clinical NLP models
Objective The evaluation of natural language processing (NLP) models for clinical text de-
identification relies on the availability of clinical notes, which is often restricted due to privacy …
identification relies on the availability of clinical notes, which is often restricted due to privacy …
[HTML][HTML] Computational interpretation of human genetic variation
Y Bromberg, P Radivojac - Human Genetics, 2022 - Springer
Computational interpretation of human genetic variants comprises the development and
application of analysis and prediction techniques aimed at elucidating the impact of variants …
application of analysis and prediction techniques aimed at elucidating the impact of variants …