Results 51 to 60 of about 261,899 (345)

Digital Twin Technology: The Future of Predicting Neurological Complications of Pediatric Cancers and Their Treatment

open access: yesFrontiers in Oncology, 2022
Healthcare technologies have seen a surge in utilization during the COVID 19 pandemic. Remote patient care, virtual follow-up and other forms of futurism will likely see further adaptation both as a preparational strategy for future pandemics and due to ...
Grace M. Thiong’o   +3 more
doaj   +1 more source

Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications

open access: yesJournal of Clinical Medicine
The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding of the brain, unlocking new possibilities in research, diagnosis, and therapy.
R. Onciul   +7 more
semanticscholar   +1 more source

Survival for Children Diagnosed With Wilms Tumour (2012–2022) Registered in the UK and Ireland Improving Population Outcomes for Renal Tumours of Childhood (IMPORT) Study

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background The Improving Population Outcomes for Renal Tumours of childhood (IMPORT) is a prospective clinical observational study capturing detailed demographic and outcome data on children and young people diagnosed with renal tumours in the United Kingdom and the Republic of Ireland.
Naomi Ssenyonga   +56 more
wiley   +1 more source

Changes in Body Composition in Children and Young People Undergoing Treatment for Acute Lymphoblastic Leukemia: A Systematic Review and Meta‐Analysis

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Ongoing evidence indicates increased risk of sarcopenic obesity among children and young people (CYP) with acute lymphoblastic leukemia (ALL), often beginning early in treatment, persisting into survivorship. This review evaluates current literature on body composition in CYP with ALL during and after treatment.
Lina A. Zahed   +5 more
wiley   +1 more source

A Survey on Optimal Transport for Machine Learning: Theory and Applications

open access: yesIEEE Access
Optimal Transport (OT) theory has seen increasing attention from the computer science community due to its potency and relevance in modeling and machine learning (ML).
Luiz Manella Pereira, M. Hadi Amini
doaj   +1 more source

Applications of artificial intelligence in orthopaedic surgery

open access: yesFrontiers in Medical Technology, 2022
The practice of medicine is rapidly transforming as a result of technological breakthroughs. Artificial intelligence (AI) systems are becoming more and more relevant in medicine and orthopaedic surgery as a result of the nearly exponential growth in ...
Faraz Farhadi   +6 more
doaj   +1 more source

Parent‐to‐Child Information Disclosure in Pediatric Oncology

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Despite professional consensus regarding the importance of open communication with pediatric cancer patients about their disease, actual practice patterns of disclosure are understudied. Extant literature suggests a significant proportion of children are not told about their diagnosis/prognosis, which is purported to negatively ...
Rachel A. Kentor   +12 more
wiley   +1 more source

Automation of Knowledge Work in Medicine and Health care: Future and Challenges

open access: yesInternational Journal of Body, Mind and Culture, 2017
Increment of computing speed, machine learning and human interface, have extended capabilities of artificial intelligence applications to an important stage. It is predicted that use of artificial intelligence (AI) to automate knowledge-based occupations
Farzan Majidfar
doaj  

Properties of CAD/CAM 3D Printing Dental Materials and Their Clinical Applications in Orthodontics: Where Are We Now?

open access: yesApplied Sciences, 2022
In the last years, both medicine and dentistry have come across a revolution represented by the introduction of more and more digital technologies for both diagnostic and therapeutic purposes.
Andrea Scribante   +8 more
doaj   +1 more source

Predicting Chronicity in Children and Adolescents With Newly Diagnosed Immune Thrombocytopenia at the Timepoint of Diagnosis Using Machine Learning‐Based Approaches

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Objectives To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individual risk of chronicity at the timepoint of diagnosis. Methods We analyzed a longitudinal cohort of 944 children enrolled in the Intercontinental Cooperative immune thrombocytopenia (ITP) Study ...
Severin Kasser   +6 more
wiley   +1 more source

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