Results 31 to 40 of about 1,106,758 (269)
Pediatric 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
UrbanBlocks 3-D: A Genetic Algorithm-Based Semantic Zoning Framework for Smart Cities
IEEE AccessUrban planning faces critical challenges with 68% of the global population projected to live in cities by 2050, requiring intelligent zoning solutions for sustainable development.
Somesh Nandi +3 more
doaj +1 more source
Artificial intelligence/machine learning in diabetes care
Indian Journal of Endocrinology and Metabolism, 2019 Artificial intelligence/Machine learning (AI/ML) is transforming all spheres of our life, including the healthcare system. Application of AI/ML has a potential to vastly enhance the reach of diabetes care thereby making it more efficient. The huge burden of diabetes cases in India represents a unique set of problems, and provides us with a unique ...
Rajiv Singla +3 more
openaire +3 more sources
Molecular Oncology, EarlyView.Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz +15 more
wiley +1 more source
Artificial intelligence and machine learning in haematology [PDF]
British Journal of Haematology, 2019 Artificial intelligence (AI) and Machine Learning (ML) are trending topics. AI is a broad term that represents the general concept of machines being able to carry out decision-making and perform human-like complex tasks, such as problem solving, understanding languages, recognizing voices and images and other “smart” tasks.
openaire +2 more sources
Examples of Artificial Perceptions in Optical Character Recognition and Iris Recognition
, 2012 This paper assumes the hypothesis that human learning is perception based, and consequently, the learning process and perceptions should not be represented and investigated independently or modeled in different simulation spaces.
A.M. Turing +6 more
core +1 more source
Molecular Oncology, EarlyView.Liquid biopsy enables minimally invasive, real‐time molecular profiling through analysis of circulating biomarkers in biological fluids. This Perspective highlights the importance of training pathologists through integrative educational programs, such as the European Masters in Molecular Pathology, to ensure effective and equitable implementation of ...
Marius Ilié +13 more
wiley +1 more source
Sensors, 2023 Allocentric semantic 3D maps are highly useful for a variety of human–machine interaction related tasks since egocentric viewpoints can be derived by the machine for the human partner. Class labels and map interpretations, however, may differ or could be
László Kopácsi +7 more
doaj +1 more source
Molecular Oncology, EarlyView.The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg +43 more
wiley +1 more source
FloBlocks: an affordable and extensible tool for tangible block programming in education
Discover EducationHigh costs often restrict access to programming education, especially in underserved communities. To address this, we introduce FloBlocks, a novel, low-cost educational tool that integrates tangible flowchart programming with computer vision.
Devansh Rathor +4 more
doaj +1 more source