Computer vision has emerged as a promising technology with numerous applications in healthcare. This systematic review provides an overview of advancements and challenges associated with computer vision in healthcare. The review highlights the application areas where computer vision has made significant strides, including medical imaging, surgical assistance, remote patient monitoring, and telehealth. Additionally, it addresses the challenges related to data quality, privacy, model interpretability, and integration with existing healthcare systems. Ethical and legal considerations, such as patient consent and algorithmic bias, are also discussed. The review concludes by identifying future directions and opportunities for research, emphasizing the potential impact of computer vision on healthcare delivery and outcomes. Overall, this systematic review underscores the importance of understanding both the advancements and challenges in computer vision to facilitate its responsible implementation in healthcare.
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http://dx.doi.org/10.1016/j.compbiomed.2024.109531 | DOI Listing |
BMC Genomics
December 2024
Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, 02-106, Poland.
Low Complexity Regions (LCRs) are segments of proteins with a low diversity of amino acid composition. These regions play important roles in proteins. However, annotations describing these functions are dispersed across databases and scientific literature.
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December 2024
Neurology, Icahn School of Medicine at Mount Sinai, New York, USA.
We used machine learning to investigate the residual visual field (VF) deficits and macula retinal ganglion cell (RGC) thickness loss patterns in recovered optic neuritis (ON). We applied archetypal analysis (AA) to 377 same-day pairings of 10-2 VF and optical coherence tomography (OCT) macula images from 93 ON eyes and 70 normal fellow eyes ≥ 90 days after acute ON. We correlated archetype (AT) weights (total weight = 100%) of VFs and total retinal thickness (TRT), inner retinal thickness (IRT), and macular ganglion cell-inner plexiform layer (GCIPL) thickness.
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December 2024
Computer Research Institute of Montreal- CRIM, Vision Research Department, Montreal, Qc., Canada.
The proliferation of deepfake generation has become increasingly widespread. Current solutions for automatically detecting and classifying generated content require substantial computational resources, making them impractical for use by the average non-expert individual, particularly from edge computing applications. In this paper, we propose a series of techniques to accelerate the inference speed of deepfake detection on video data.
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December 2024
Department of Ophthalmology, Jinshan Hospital of Fudan University, 1508 Longhang Road, Jinshan District, Shanghai, China.
To observe the structural changes of retina and choroid in patients with different degrees of myopia. We recruited 219 subjects with different degrees of myopia for best corrected visual acuity, computer refraction, intraocular pressure, axial length (AL), optical coherence tomography (OCT) imaging, and other examinations. Central macular retinal thickness (CRT), subfoveal choroidal thickness (SFCT), nasal retinal thickness (NRT), temporal retinal thickness (TRT), nasal choroidal thickness (NCT) and temporal choroidal thickness (TCT) were measured by optical coherence tomography.
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December 2024
National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, 430070, P. R. China.
Point cloud analysis is a crucial task in computer vision. Despite significant advances over the past decade, the developments in agricultural domain have faced challenges due to a scarcity of datasets. To facilitate 3D point cloud research in agriculture community, we introduce Crops3D, the diverse real-world dataset derived from authentic agricultural scenarios.
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