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Mashup Score: 12The use of weakly supervised machine learning for necrosis assessment in patients with osteosarcoma: A pilot study - 6 month(s) ago
Percent necrosis (PN) following chemotherapy is a prognostic factor for survival in osteosarcoma. Pathologists estimate PN by calculating tumor viability over an average of whole-slide images (WSIs)….
Source: onlinelibrary.wiley.comCategories: General Medicine News, General NewsTweet
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Mashup Score: 6Use of machine learning to identify risk factors for insomnia - 1 year(s) ago
Importance Sleep is critical to a person’s physical and mental health, but there are few studies systematically assessing risk factors for sleep disorders. Objective The objective of this study was to identify risk factors for a sleep disorder through machine-learning and assess this methodology. Design, setting, and participants A retrospective, cross-sectional cohort study using the…
Source: journals.plos.orgCategories: General Medicine News, Latest HeadlinesTweet-
Decoding insomnia: #Machinelearningmodel predicts #sleepdisorders from patient records @PLOSONE https://t.co/gCmcuWF0xw https://t.co/vJUpmoSmjB
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Mashup Score: 4
This prognostic study uses machine learning to estimate the risk of adverse outcomes within 30 days of opioid dispensation in Alberta, Canada, as a potential component of prescription drug monitoring programs to identify and intervene in cases of high-risk opioid prescribing.
Source: jamanetwork.comCategories: General Medicine News, Latest HeadlinesTweet-
#Machinelearningmodel helps doctors predict opioid prescription risk for #patients @ualberta @jamanetworkopen https://t.co/kK2e2oz0Kc https://t.co/IHaia7BsAM
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Mashup Score: 9Predicting physician departure with machine learning on EHR use patterns: A longitudinal cohort from a large multi-specialty ambulatory practice - 1 year(s) ago
Physician turnover places a heavy burden on the healthcare industry, patients, physicians, and their families. Having a mechanism in place to identify physicians at risk for departure could help target appropriate interventions that prevent departure. We have collected physician characteristics, electronic health record (EHR) use patterns, and clinical productivity data from a large ambulatory…
Source: journals.plos.orgCategories: General Medicine News, Latest HeadlinesTweet-
#Machinelearningmodel predicts physician turnover @yale @PLOSONE https://t.co/jtB4TtcywG https://t.co/wXc4eU4Zou
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Researchers create #machineLearningModel to calculate chemotherapy success in patients with osteosarcoma https://t.co/gPgIgKK4NT https://t.co/KIg8oq7FG0