Results 191 to 200 of about 356,920 (284)

Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo   +4 more
wiley   +1 more source

[Social determinants of health: alternative explanatory proposal to the biomedical approach to suicidal behavior]. [PDF]

open access: yesRev Salud Publica (Bogota)
Hernández-Bello LS   +2 more
europepmc   +1 more source

Psoas Muscle Volume as a Predictor of Postoperative Complications in Patients Undergoing Emergency Surgery for Strangulated Small Bowel Obstruction: A Retrospective Single‐Center Study

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
This retrospective study identified low preoperative psoas muscle volume, measured by computed tomography, as an independent predictor of postoperative complications in patients undergoing emergency surgery for strangulated small bowel obstruction. Low psoas muscle volume, particularly in older adults, was associated with cardiopulmonary and systemic ...
Takuya Shiraishi   +9 more
wiley   +1 more source

[Evaluation of a coding guide on social determinants of health in primary care consultations: A mixed study]. [PDF]

open access: yesAten Primaria
Rodoreda-Pallàs B   +5 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Determinantes sociales en la salud de la familia cubana

open access: yesMedisan
La medicina incrementa continuamente su enfoque social, donde la familia, como célula fundamental de la sociedad, resulta un objeto de trabajo esencial para el equipo de salud, pues posee una incidencia importante en el desarrollo del proceso salud ...
Maritza del Carmen Berenguer Gouarnaluses   +3 more
doaj  

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

open access: yesAdvanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova   +4 more
wiley   +1 more source

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