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Highly accurate protein structure prediction with AlphaFold
Abstract Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort ...
Basics of qualitative research : techniques and procedures for developing grounded theory
Part I: Introduction to Grounded Theory of Anselm Strauss Chapter 1: Inspiration and Background Chapter 2: Theoretical Foundations Chapter 3: Practical Considerations for Gettin...
An Inventory for Measuring Depression
The difficulties inherent in obtaining consistent and adequate diagnoses for the purposes of research and therapy have been pointed out by a number of authors. Pasamanick<sup>12...
Fully convolutional networks for semantic segmentation
Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, ex...
The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection.
A 36-item short-form (SF-36) was constructed to survey health status in the Medical Outcomes Study. The SF-36 was designed for use in clinical practice and research, health poli...
PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
Scoping reviews, a type of knowledge synthesis, follow a systematic approach to map evidence on a topic and identify main concepts, theories, sources, and knowledge gaps. Althou...
Clinical Characteristics of Coronavirus Disease 2019 in China
BACKGROUND: Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical charac...
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that...
Rethinking the Inception Architecture for Computer Vision
Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to bec...