Results 61 to 70 of about 8,106,141 (300)

Ovarian Sex Cord Stromal Tumors in Children and Adolescents—The European Standard Clinical Practice Recommendations

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT As part of the European Cooperative Study Group for Paediatric Rare Tumours initiative, we developed standard clinical practice guidelines for ovarian sex cord stromal tumors, based on comprehensive national and international cohort analyses, literature review, and a final expert consensus conference.
Dominik T. Schneider   +15 more
wiley   +1 more source

Signal reproduction of acceleration sensor data for physical activity recognition

open access: yes, 2022
S.36-41This paper addresses the challenges of flexible acceleration sensor sampling rates of mobile phones and describes the problem of signal reproduction of blurred or distorted signals for physical activity recognition.
Wacker, Fred, Bieber, Gerald
core   +1 more source

Badminton Activity Recognition Using Accelerometer Data

open access: yesSensors, 2020
A thorough analysis of sports is becoming increasingly important during the training process of badminton players at both the recreational and professional level.
Tim Steels   +5 more
doaj   +1 more source

Evidence‐Informed Multidisciplinary Consensus Guidance for the Psychosocial Care of Adolescents With High‐Risk Cancer: Recommendations From the Italian Association of Pediatric Hematology and Oncology

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Adolescents with high‐risk cancer face complex developmental, psychosocial, and ethical challenges that extend beyond disease‐directed treatment. Although international recommendations exist for communication, psychosocial care, pediatric palliative care, survivorship, and shared decision‐making, these have largely evolved within ...
Johanna M. C. Blom   +15 more
wiley   +1 more source

Recognition of Human Activities Using Depth Maps and the Viewpoint Feature Histogram Descriptor

open access: yesSensors, 2020
In this paper we propose a way of using depth maps transformed into 3D point clouds to classify human activities. The activities are described as time sequences of feature vectors based on the Viewpoint Feature Histogram descriptor (VFH) computed using ...
Kamil Sidor, Marian Wysocki
doaj   +1 more source

Periodic Physical Activity Information Segmentation, Counting and Recognition From Video

open access: yesIEEE Access, 2023
The research on complex human body motion including sports and workout activity recognition is a major challenge and long-lasting problem for the computer vision community.
Sheng-Hsien Cheng   +4 more
doaj   +1 more source

Bridging the Loneliness Gap: Depression, Connectivity, and Isolation in Pediatric Oncology Patients and Their Peers

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Loneliness is associated with adverse physical and mental health outcomes and remains understudied in children and adolescents undergoing cancer therapy. Pediatric oncology patients may be at increased risk due to medical isolation and disruption of social networks.
Charlotte N. Stahlfeld   +5 more
wiley   +1 more source

Opportunities for activity recognition using ultrasound doppler sensing on unmodified mobile phones

open access: yes, 2022
Art. 8, 10 S.Nowadays activity recognition on smartphones is ubiquitously applied, for example to monitor personal health. The smartphone's sensors act as a foundation to provide information on movements, the user's location or direction.
Karolus, Jakob   +4 more
core   +1 more source

Communicating Recognition & Rewards experiences: Tips and tricks

open access: yes
These guidelines support communications and marketing employees in the preparation and execution stages of creating a story about someone’s experiences with Recognition & Rewards (R&R) principles and themes.
Recognition & Rewards
core   +2 more sources

Cost-Effective Multitask Active Learning in Wearable Sensor Systems

open access: yesSensors
Multitask learning models provide benefits by reducing model complexity and improving accuracy by concurrently learning multiple tasks with shared representations.
Asiful Arefeen, Hassan Ghasemzadeh
doaj   +1 more source

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