In Reply We thank Shigematsu and Inamura for the opportunity to enlarge the debate about our last published algorithm. 1 An interesting consequence of analyzing large real-life data is observing the real trends in a specific cohort beyond randomized clinical trials or expert guidelines. Such data provide a snapshot, summing all the differences present in the …
WhatsApp: +86 18221755073In this issue of JAMA, Liu and colleagues 1 provide a users' guide to reading clinical machine learning articles. Beyond a synopsis of selected concepts in modern machine learning, the authors elaborate step-by-step guidance for physicians seeking to evaluate this evidence with a critical eye.
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WhatsApp: +86 18221755073A total of 41 randomized clinical trials were included in the analysis. 26-66 Individuals from underrepresented minority groups were participants in 11 clinical trials in which information on participant race and/or ethnicity was reported. 30-33,36,44,49,55,59,61,63 B, Data for 2021 are from January through October 15. D, The other medical specialty category …
WhatsApp: +86 18221755073Machine learning–based tools should also be assessed for the type of machine learning model used and its appropriateness for the input data type and data set size. Machine learning models also generally have additional prespecified settings called hyperparameters, which must be tuned on a data set independent of the validation set.
WhatsApp: +86 18221755073Key Points. Question Can machine learning models accurately predict patient disability and pain following lumbar disc herniation surgery?. Findings In this prognostic study including 22 707 patients, machine learning models were developed and validated in large-scale, nationally representative data for treatment success or nonsuccess in disability and pain …
WhatsApp: +86 18221755073 JAMA. 2000;284(7):835-842. doi: ... Some machine learning models may, therefore, have greater clinical utility in higher-dimensional data where they can uncover complex relationships among variables 30-32 and of variables with outcomes but only provide limited gains in relatively low-dimension registry data. Furthermore, not all machine ...
WhatsApp: +86 18221755073A Machine Learning Approach for Automated Facial Measurements in Facial Palsy JAMA Facial Plast Surg. 2018 Jul 1;20(4):335-337. doi: 10.1001/jamafacial.2018.0030. Authors Diego L Guarin 1, Joseph Dusseldorp 1 2, Tessa A Hadlock 1, Nate Jowett 1 Affiliations 1 Department of Otolaryngology, Massachusetts ...
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WhatsApp: +86 18221755073A total of 41 randomized clinical trials were included in the analysis. 26-66 Individuals from underrepresented minority groups were participants in 11 clinical trials in which …
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WhatsApp: +86 18221755073Over the past decade, machine learning techniques have made substantial advances in many domains. In health care, global interest in the potential of machine learning has increased; for example, a deep learning algorithm has shown high accuracy in detecting diabetic retinopathy. 1 There have been suggestions that machine learning will drive …
WhatsApp: +86 18221755073Machine learning for prediction in electronic health data has been deployed for many clinical questions during the last decade. Machine learning methods may excel at finding new features or nonlinear relationships in the data, as well as handling settings with more predictor variables than observations.
WhatsApp: +86 18221755073Key Points. Question Can multitask machine learning be used to better understand open surgical technique?. Findings This study presented a multitask neural network for visual understanding of open surgeries and introduces a data set used to train the model. It illustrated the utility of the model to generate procedure-specific signatures and identify …
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WhatsApp: +86 18221755073Machine learning (ML), a form of artificial intelligence using computer algorithms, is often applied in ways we take for granted: Spotify to predict music that people may enjoy, Facebook to suggest friends to tag in photos, and Amazon to identify products to buy.
WhatsApp: +86 18221755073Machine Learning and the Profession of Medicine. Machine Learning and the Profession of Medicine. Machine Learning and the Profession of Medicine JAMA. 2016 Feb 9;315(6):551-2. doi: 10.1001/jama.2015.18421. Authors Alison M Darcy 1, Alan K Louie 1, Laura Weiss Roberts 1 Affiliation 1 Department of ...
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WhatsApp: +86 18221755073Key Points. Question Does an intervention consisting of machine learning mortality predictions and behavioral nudges to oncology clinicians have an impact on serious illness conversations (SICs) and end-of-life outcomes among patients with cancer?. Findings In this randomized clinical trial that included 20 506 patients with cancer (for a total of 41 …
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WhatsApp: +86 18221755073The staggering cost of cancer treatment has led to widespread calls for changes in care delivery. 1 After nearly 50 years, the war on cancer has resulted in breakthrough treatments and survival improvements for multiple cancers. 1 Corresponding advances in care delivery, however, lag far behind.
WhatsApp: +86 182217550732019 Nov 12;322(18):1777-1779. doi: 10.1001/jama.2019.17304. Authors Finale Doshi-Velez 1, Roy H Perlis 2 Affiliations 1 Harvard University, Boston, Massachusetts. 2 Massachusetts General Hospital, Boston. PMID: 31714974 DOI: 10.1001 ... Machine Learning* Publications* ...
WhatsApp: +86 18221755073Key Points. Question Can a machine-leaning approach improve the accuracy of predicting the risk for readmission at 30 days in hospitalized patients with heart failure?. Findings In this registry-based modelling study, the accuracy and discrimination of 3 machine-learning approaches (least absolute shrinkage and selection operator, random forest, and …
WhatsApp: +86 18221755073Importance Machine learning (ML) algorithms have the potential to identify eyes with early diabetic retinopathy (DR) at increased risk for disease progression.. Objective To create and validate automated ML models (autoML) for DR progression from ultra-widefield (UWF) retinal images.. Design, Setting and Participants Deidentified UWF images with mild or …
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WhatsApp: +86 18221755073Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial ... (11):1052-1060. doi: 10.1001/jama.2020.0592. Authors Marije Wijnberge 1 2, Bart F Geerts 1, ...
WhatsApp: +86 18221755073Importance Among critically ill adults, randomized trials have not found oxygenation targets to affect outcomes overall. Whether the effects of oxygenation targets differ based on an individual's characteristics is unknown. Objective To determine whether an individual's characteristics modify the effect of lower vs higher peripheral oxygenation-saturation (Sp …
WhatsApp: +86 18221755073The Case for Algorithmic Stewardship for Artificial Intelligence and Machine Learning Technologies. ... 2020 Oct 13;324(14):1397-1398. doi: 10.1001/jama.2020.9371. Authors Stephanie Eaneff 1 2, Ziad Obermeyer 3, Atul J Butte 2 4 Affiliations 1 Berkeley Institute for Data Science, University of California, Berkeley. 2 Bakar ...
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WhatsApp: +86 18221755073Normothermic Machine Perfusion Increases Donor Liver Use. ... JAMA Surg. 2022 May 4. doi: 10.1001/jamasurg.2022.1424. Online ahead of print. Authors James F Markmann 1, Parsia A Vagefi 2, Malcolm P MacConmara 3 Affiliations 1 Massachusetts General Hospital, Boston. 2 University of ...
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