Results 11 to 20 of about 1,803,952 (383)
Semi‐supervised classification of fundus images combined with CNN and GCN
Abstract Purpose Diabetic retinopathy (DR) is one of the most serious complications of diabetes, which is a kind of fundus lesion with specific changes. Early diagnosis of DR can effectively reduce the visual damage caused by DR. Due to the variety and different morphology of DR lesions, automatic classification of fundus images in mass screening can ...
Sixu Duan+8 more
wiley +1 more source
Abstract Purpose A set of treatment planning strategies were designed and retrospectively implemented for locally advanced, non‐small cell lung cancer (NSCLC) patients in order to minimize cardiac dose without compromising target coverage goals. Methods Retrospective analysis was performed for 20 NSCLC patients prescribed to 60–66 Gy that received a ...
Joshua P. Kim+5 more
wiley +1 more source
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
Introduction Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advancements
Shuroug A. Alowais+12 more
semanticscholar +1 more source
Numerous technical—scientific reports have demonstrated that student performance variability is linked to several factors, especially socioeconomic factors. For a century, differential psychology has shown that students’ socioeconomic level has little or
Carmen Flores-Mendoza+4 more
doaj +1 more source
Abstract Positron emission tomography with x‐ray computed tomography (PET/CT) is increasingly being utilized for radiation treatment planning (RTP). Accurate delivery of RT therefore depends on quality PET/CT data. This study covers quality control (QC) procedures required for PET/CT for diagnostic imaging and incremental QC required for RTP.
Ran Klein+7 more
wiley +1 more source
Explainable Artificial Intelligence (XAI)
Explainable Artificial Intelligence (XAI) has emerged as a critical facet in the realm of machine learning and artificial intelligence, responding to the increasing complexity of models, particularly deep neural networks, and the subsequent need for ...
Ranu Sewada+3 more
semanticscholar +1 more source
Background: Low intelligence has been shown to be associated with a high risk of cardiovascular disease in observational studies. It remains unclear whether the association is causal.
Fangkun Yang+5 more
doaj +1 more source
Foundation models for generalist medical artificial intelligence
The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI) models is likely to usher in newfound capabilities in medicine.
Michael Moor+6 more
semanticscholar +1 more source
Intelligence Quotient and Intelligence Grade of Artificial Intelligence [PDF]
Although artificial intelligence is currently one of the most interesting areas in scientific research, the potential threats posed by emerging AI systems remain a source of persistent controversy. To address the issue of AI threat, this study proposes a standard intelligence model that unifies AI and human characteristics in terms of four aspects of ...
Ying Liu, Feng Liu, Yong Shi
openaire +3 more sources
The challenge of crafting intelligible intelligence [PDF]
To trust the behavior of complex AI algorithms, especially in mission-critical settings, they must be made intelligible.
Daniel S. Weld, Gagan Bansal
openaire +3 more sources