Machine Learning For Pediatric Health
Listing Websites about Machine Learning For Pediatric Health
Machine Learning for Child and Adolescent Health: A …
(2 days ago) WEBZahra Hoodbhoy, Sarah Masroor Jeelani, Abeer Aziz, Muhammad Ibrahim Habib, Bilal Iqbal, Waqaas Akmal, Khan Siddiqui, Babar Hasan, Mariska Leeflang, Jai K. Das; Machine Learning for Child and Adolescent Health: A Systematic Review. …
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Machine Learning for Child and Adolescent Health: A …
(1 days ago) WEBAbstract. Context: In the last few decades, data acquisition and processing has seen tremendous amount of growth, thus sparking interest in machine learning (ML) within the health care system. Objective: Our aim for this review is to provide an evidence map of the current available evidence on ML in pediatrics and adolescent medicine and
https://pubmed.ncbi.nlm.nih.gov/33323492/
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Improving child health through Big Data and data science …
(Just Now) WEBPEDSnet is a national pediatric learning health system with a multi-specialty network of collaborators from Children’s Hospitals across the United States. 40 Using a common data model from its
https://www.nature.com/articles/s41390-022-02264-9
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The use of machine learning and artificial intelligence …
(Just Now) WEBSeveral groups have started to define machine learning algorithms to predict the development of sepsis or septic shock in pediatric inpatients. 52,53,54 This is in addition to the use of machine
https://www.nature.com/articles/s41390-022-02380-6
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Machine Learning and Artificial Intelligence in Pediatric …
(Just Now) WEBMachine learning is increasingly used to analyze information generated by electronic health record systems and other large public health datasets.1,2 It is a field of artificial intelligence that uses pattern recognition and computer modeling to uncover complex nonlinear relationships existing among independent and dependent variables. Machine …
https://www.jpeds.com/article/S0022-3476(20)30253-5/fulltext
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Machine learning approaches to predicting no-shows in …
(Just Now) WEBWe retrospectively collected records from 161,822 hospital appointments made by 19,450 patients between January 10th, 2015 and September 9th, 2016 at Boston Children’s Hospital’s primary care
https://www.nature.com/articles/s41746-022-00594-w
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Artificial intelligence and machine learning in pediatrics …
(3 days ago) WEBMachine learning surpassed the Pediatric Logistic Organ Dysfunction score (PELOD-2) in the prediction of severe sepsis 4 h before the start of the treatment. Machine learning systems in healthcare may be prone to algorithmic bias, such as predicting a higher risk of disease based on gender or ethnicity when those aspects are …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575899/
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Artificial Intelligence and Machine Learning in Pediatrics
(7 days ago) WEBOver the past few decades, large volumes of healthcare data in different formats with multiple dimensions and complexities (i.e., the 10 Vs of Big Data), beyond the comprehension of human capacity have been created exponentially. New intelligent tools and methods are required to exploit these data volumes, particularly obtained using …
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From Clinic to Computer and Back Again: Practical
(Just Now) WEBPurpose of review Machine learning (ML), a branch of artificial intelligence, is influencing all fields in medicine, with an abundance of work describing its application to adult practice. ML in pediatrics is distinctly unique with clinical, technical, and ethical nuances limiting the direct translation of ML tools developed for adults to pediatric …
https://link.springer.com/article/10.1007/s40746-020-00205-4
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Recommendations for the use of pediatric data in artificial
(4 days ago) WEBThe interests of children must be protected in artificial intelligence research. While a number of medical devices have been formally licensed for usage in children, there remains to date no guidance on the ethical use of pediatric data in artificial intelligence or machine learning (AI/ML) research 1.To ensure fundamental ethical principles are …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482936/
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Artificial Intelligence in Pediatrics SpringerLink
(4 days ago) WEBPast medical histories are also often naturally simpler than with adults. As a result, the pediatric patient population is generally less heterogeneous, making machine learning projects potentially more straightforward to design and execute. Pediatric health records are also relatively more complete than those for adults.
https://link.springer.com/referenceworkentry/10.1007/978-3-030-64573-1_316
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Artificial Intelligence in Pediatric Cardiology: A Scoping Review
(3 days ago) WEBThe evolution of deep learning models and machine learning models and the establishment of defined pediatric datasets have allowed the entry of AI for use in the pediatric population . AI can be immensely beneficial in various steps of imaging such as ordering tests, reporting communication, enhancing the quality of images, and aiding
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738645/
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Machine learning enables update to pediatric neurorehabilitation
(9 days ago) WEBAt the cutting edge of this transformation stands artificial intelligence, which has presented the potential to significantly enhance healthcare outcomes. As a pivotal branch of artificial intelligence, machine learning (ML) involves the development of intelligent algorithms with self-improvement through experience.
https://onlinelibrary.wiley.com/doi/full/10.1002/ped4.12418
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Future of machine learning in paediatrics Archives of Disease in
(7 days ago) WEBMachine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn without being explicitly programmed, through a combination of statistics and computer science. It encompasses a variety of techniques used to analyse and interpret extremely large amounts of data, which can then be applied to create predictive models. Such …
https://adc.bmj.com/content/107/3/223
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Artificial Intelligence and the Future of Pediatric Health Care
(3 days ago) WEBThis webinar, tailored to pediatric health care executives, delves into the dynamic world of generative artificial intelligence. At one children’s hospital, a machine learning algorithm identifies malnutrition in patients with up to …
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How Machine Learning Experts and Physicians at Johns Hopkins …
(7 days ago) WEB“Deep Anesthesia: Toward Improving Post-Operative Anesthesia Complications Using Deep Learning,” presented at the Machine Learning for Healthcare conference Aug. 7-8. “Machine Learning and Artificial Intelligence in Pediatric Research: Current State, Future Prospects, and Examples in Perioperative and Critical Care,” …
https://www.hopkinsmedicine.org/news/articles/2020/11/how-machine-learning-experts-and-physicians
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(PDF) Machine Learning in Pediatrics: Evaluating Challenges
(6 days ago) WEBMachine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn without being explicitly programmed, through a combination of statistics and computer science.
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Johns Hopkins All Children’s Researchers Develop Predictive, …
(4 days ago) WEBAccording to the study authors, the ASA-PS offers a “population” perspective on risk while the machine learning models offer an “individual” perspective, one where individual pediatric patient health and demographic features are programmed into the machine learning process, offering an improved, “personalized medicine” approach.
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Artificial intelligence in pediatrics: the future is now
(Just Now) WEBBeam, A. L. & Kohane, I. S. Big data and machine learning in health care. Jama 319 , 1317–1318 (2018). Article PubMed Google Scholar
https://www.nature.com/articles/s41390-022-01972-6
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Machine learning for hospital readmission prediction in pediatric
(7 days ago) WEBPediatric readmissions are a burden on patients, families, and the healthcare system. In order to identify patients at higher readmission risk, more accurate techniques, as machine learning (ML), could be a good strategy to expand the knowledge in this area. The aim of this study was to develop predictive models capable of …
https://www.sciencedirect.com/science/article/pii/S0169260723006466
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A machine learning framework for interpretable predictions
(Just Now) WEBProactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage a patient’s complete health history to make informed decisions about future events. However, previous work has mostly relied on so-called black-box models, which …
https://link.springer.com/article/10.1007/s10729-024-09673-8
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Improved pediatric ICU mortality prediction for respiratory …
(2 days ago) WEBThe growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric illnesses, there is a pressing need to predict ICU mortality in these cases. This study based on data from 1188 patients, …
https://respiratory-research.biomedcentral.com/articles/10.1186/s12931-024-02753-x
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Healthcare's Hope in Artificial Intelligence - Medscape
(Just Now) WEBThe Centers for Medicare & Medicaid Services (CMS) report a 4.1% increase in US healthcare spending in 2022, reaching a total of $4.5 trillion. Although that may seem like a modest amount, the US
https://www.medscape.com/viewarticle/healthcares-hope-artificial-intelligence-2024a10009pu
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Using large language models to protect pediatric health information
(6 days ago) WEBUSING LLMs TO PREVENT PEDIATRIC DATA DISCLOSURES. Pageler’s research involves using LLMs to prevent pediatric data disclosures by flagging confidential content in patients’ clinical notes. She indicated that AI and machine learning techniques have previously been deployed successfully to achieve this goal. “Usually, our goal is to …
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OHSU receives $16.4 million to advance mental health care for …
(2 days ago) WEBA team of researchers at Oregon Health & Science University were awarded a landmark five-year, $16.4 million grant from the National Institute of Mental Health to develop and test data-driven approaches that can more precisely predict mental health diagnoses and outcomes in children. For over a decade, experts at the OHSU Center for …
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Screening and Identification of Neutrophil Extracellular Trap
(1 days ago) WEBScreening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning Inflammation. 2024 May 25. doi: 10.1007/s10753-024-02059-6. Online ahead of print. Authors LHGJ20230209/Henan Provincial Health and Health Commission Joint Construction Project
https://pubmed.ncbi.nlm.nih.gov/38795170/
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[2405.14567] EHRMamba: Towards Generalizable and Scalable …
(2 days ago) WEBTransformers have significantly advanced the modeling of Electronic Health Records (EHR), yet their deployment in real-world healthcare is limited by several key challenges. Firstly, the quadratic computational cost and insufficient context length of these models pose significant obstacles for hospitals in processing the extensive medical …
https://arxiv.org/abs/2405.14567
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Scientists leverage machine learning to decode gene regulation in …
(3 days ago) WEBSean Whalen, Ph.D., a senior research scientist in the Pollard Lab at Gladstone and a co-first author of the study, says the team tested the machine learning model using sequences held out from
https://medicalxpress.com/news/2024-05-scientists-leverage-machine-decode-gene.html
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Artificial intelligence-based clinical decision support in pediatrics
(Just Now) WEBSingh, D. et al. Assessment of machine learning–based medical directives to expedite care in pediatric emergency medicine. JAMA Netw. Open 5 , e222599–e222599 (2022).
https://www.nature.com/articles/s41390-022-02226-1
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Predicting fracture risk for elderly osteoporosis patients by hybrid
(8 days ago) WEBDemographic and clinical features were used to develop prediction models based on 12 independent machine learning (ML) algorithms and 3 hybrid ML models. To facilitate a nuanced interpretation of the results, a comprehensive importance score was conceived, incorporating various perspectives to effectively discern and mine critical …
https://journals.sagepub.com/doi/10.1177/20552076241257456
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Pitt physicians on the big screen Pitt Med Magazine University …
(5 days ago) WEBDante, a teenager, suffers from abdominal pain in the emergency room. He has just been arrested. While everyone dismisses his symptoms, thinking that he is faking them to avoid going to jail, he plays with a Rubik’s Cube. This scene comes from “In Good Hands,” a short film based on the memoir of Sylvia Owusu-Ansah, an MD, MPH Pitt …
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Treatment and Intervention for Hearing Loss
(2 days ago) WEBTreatment and intervention options for hearing loss in children include. Working with a professional (or team) who can help a child and family learn to communicate. Getting a hearing device, such as a hearing aid. Joining support groups. Taking advantage of other resources available to children with a hearing loss and their …
https://www.cdc.gov/hearing-loss-children/treatment/index.html
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Redox, Snowflake Partner to Streamline Healthcare Data Exchange …
(8 days ago) WEBRedox, a healthcare interoperability company, and Snowflake have joined forces to simplify the exchange of healthcare data for AI/ML Redox, a healthcare interoperability company, and Snowflake
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Evaluation and accurate diagnoses of pediatric diseases using
(9 days ago) WEBAlthough machine learning classifiers (MLCs) have already demonstrated strong performance in image-based diagnoses, analysis of diverse and massive electronic health record (EHR) data remains
https://www.nature.com/articles/s41591-018-0335-9
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Children’s Health and UT Southwestern receive $100 million …
(3 days ago) WEBDALLAS – May 15, 2024 – Children's Health SM and UT Southwestern Medical Center on Wednesday announced a historic gift of $100 million from the Jean and Mack Pogue family in support of the $5 billion transformative new Dallas pediatric campus, unveiled earlier this year. The gift from the Pogue Foundation is one of only four $100 million philanthropic …
https://www.utsouthwestern.edu/newsroom/articles/year-2024/may-donor-milestone.html
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About Adverse Childhood Experiences Adverse Childhood …
(1 days ago) WEBToxic stress, or extended or prolonged stress, from ACEs can negatively affect children’s brain development, immune systems, and stress-response systems. These changes can affect children’s attention, decision-making, and learning. 18. Children growing up with toxic stress may have difficulty forming healthy and stable relationships.
https://www.cdc.gov/aces/about/index.html
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