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Pancreatic cancer: a haystack of needles.
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Surgical Oncology Division, Department of General Surgery, Walter Reed National Military Medical Center, Bethesda, MD, USA.
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Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH.
Finding a Needle in a Haystack: A Systematic Approach for Searching Through Public Databases for Youth Mental Well-Being Programs.
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Margaret and Wallace McCain Centre for Child, Youth and Family Mental Health at the Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
Background: This practice paper exemplifies a systematic approach used to learn about existing mental well-being programs for youth 11-14 years to inform curriculum development for after-school settings.
Methods: We reviewed 3389 mental well-being programs from publicly accessed databases and conducted a content analysis using inductive and deductive coding to explore the domains each program addressed.
Results: Through our content analysis of the final eight programs, we found strong alignment with the Collaborative for Academic, Social and Emotional Learning (CASEL) core social-emotional competencies: self-awareness, self-management, social awareness, relationship skills, and decision-making.
Defining the needle in a haystack: A compendium of genomic, pathologic, and clinical characteristics of rare pulmonary tumors.
Lung Cancer
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Department of Internal Medicine, Division of Hematology/Oncology, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indiana University School of Medicine (IUSOM), Indianapolis, IN 46202, USA. Electronic address:
A major paradigm shift in the diagnosis, management, and survival outcomes of early and advanced non-small cell lung cancer has transpired over the past few decades in thoracic oncology with the incorporation of molecular testing, targeted therapy, immunotherapy, neoadjuvant, and adjuvant approaches. However, transformation in the management and survival outcomes of rare lung tumors is lacking. Given the scarcity of these tumor types, randomized trials are rarely performed, and treatment is extrapolated from case series, tumor-agnostic trials, or cancers with similar histology.
View Article and Find Full Text PDFFinding the needle in the haystack of isokinetic knee data: Random Forest modelling improves information about ACLR-related deficiencies.
J Sports Sci
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Department of Biomechanics, Performance Analysis and Strength & Conditioning, Olympic Training & Testing Centre Westphalia, Dortmund, Germany.
The difficulties of rehabilitation after anterior cruciate ligament (ACL) injuries, subsequent return-to-sport (RTS) let alone achieving pre-injury performance, are well known. Isokinetic testing is often used to assess strength capacities during that process. The aim of the present machine learning (ML) approach was to examine which isokinetic data differentiates athletes post ACL reconstruction (ACLR) and healthy controls.
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