Results 131 to 140 of about 4,525,334 (379)

Novel CT radiomics models for the postoperative prediction of early recurrence of resectable pancreatic adenocarcinoma: A single‐center retrospective study in China

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose To assess the predictive capability of CT radiomics features for early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC). Methods Postoperative PDAC patients were retrospectively selected, all of whom had undergone preoperative CT imaging and surgery. Both patients with resectable or borderline‐resectable pancreatic cancer met
Xinze Du   +7 more
wiley   +1 more source

Developing reference plans for evaluating global clinical trials credentialing and PSQA systems

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose To develop a practical framework for creating a diverse set of validated reference plans (varying in complexity) and implement a workflow to introduce beam modeling, calibration, and delivery errors into the reference cohort to test and compare various dosimetry audit methodologies.
Fre'Etta M. D. Brooks   +13 more
wiley   +1 more source

Minimizando perdas e maximizando eficiência na detecção de casos de desnutrição aguda severa

open access: yesRevista de Saúde Pública
OBJETIVO: Alguns dos muitos desafios enfrentados por epidemiologistas são planejar adequadamente e otimizar o processo de captação de sujeitos em termos de efetividade e eficiência.
Michael E Reichenheim   +1 more
doaj  

Generalized Simple Graphical Rules for Assessing Selection Bias [PDF]

open access: yesarXiv
Selection bias is a major obstacle toward valid causal inference in epidemiology. Over the past decade, several simple graphical rules based on causal diagrams have been proposed as the sufficient identification conditions for addressing selection bias and recovering causal effects.
arxiv  

Theory on Covariate-Adaptive Randomized Clinical Trials: Efficiency, Selection bias and Randomization Methods [PDF]

open access: yesarXiv, 2019
The theocratical properties of the power of the conventional testing hypotheses and the selection bias are usually unknown under covariate-adaptive randomized clinical trials. In the literature, most studies are based on simulations. In this article, we provide theoretical foundation of the power of the hypothesis testing and the selection bias under ...
arxiv  

The burden of burnout: Understanding its prevalence and organizational drivers in medical physics

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Background Burnout is a work‐related syndrome characterized by increased levels of emotional exhaustion (EE) and depersonalization (DP) along with decreased levels of personal achievement. In the healthcare setting, higher burnout levels have been associated with negative impacts on personnel, an increased risk of errors, and a decrease in the
Deborah Schofield   +4 more
wiley   +1 more source

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning [PDF]

open access: yesarXiv
Selection bias poses a critical challenge for fairness in machine learning, as models trained on data that is less representative of the population might exhibit undesirable behavior for underrepresented profiles. Semi-supervised learning strategies like self-training can mitigate selection bias by incorporating unlabeled data into model training to ...
arxiv  

Empowering young minds through STEM education: Engaging high schoolers in Ghana through medical physics

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose To promote diversity in Science, Technology, Engineering, and Mathematics (STEM), an educational presentation and hands‐on session was organised to raise awareness of STEM career opportunities among high school girls to introduce the students to the field of medical physics. Materials and Methods The study involved 65 first‐year Senior
Afua A. Yorke   +7 more
wiley   +1 more source

Selective Inference Approach for Statistically Sound Predictive Pattern Mining [PDF]

open access: yesarXiv, 2016
Discovering statistically significant patterns from databases is an important challenging problem. The main obstacle of this problem is in the difficulty of taking into account the selection bias, i.e., the bias arising from the fact that patterns are selected from extremely large number of candidates in databases.
arxiv  

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