Human activity recognition in artificial intelligence framework: a narrative review

N Gupta, SK Gupta, RK Pathak, V Jain… - Artificial intelligence …, 2022 - Springer
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …

Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review

B Jena, S Saxena, GK Nayak, L Saba, N Sharma… - Computers in Biology …, 2021 - Elsevier
Background Artificial intelligence (AI) has served humanity in many applications since its
inception. Currently, it dominates the imaging field—in particular, image classification. The …

Intelligent model to predict early liver disease using machine learning technique

TM Ghazal, AU Rehman, M Saleem… - … for Technology and …, 2022 - ieeexplore.ieee.org
Liver Disease (LD) is the main cause of death worldwide, affecting a large number of
people. A variety of factors affect the liver, resulting in this disease. The diagnosis of this …

[HTML][HTML] Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction

D Nam, J Chapiro, V Paradis, TP Seraphin, JN Kather - Jhep Reports, 2022 - Elsevier
Clinical routine in hepatology involves the diagnosis and treatment of a wide spectrum of
metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative …

A review on a deep learning perspective in brain cancer classification

GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri… - Cancers, 2019 - mdpi.com
A World Health Organization (WHO) Feb 2018 report has recently shown that mortality rate
due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It …

The present and future of deep learning in radiology

L Saba, M Biswas, V Kuppili, EC Godia, HS Suri… - European journal of …, 2019 - Elsevier
Abstract The advent of Deep Learning (DL) is poised to dramatically change the delivery of
healthcare in the near future. Not only has DL profoundly affected the healthcare industry it …

Artificial intelligence in ultrasound

YT Shen, L Chen, WW Yue, HX Xu - European Journal of Radiology, 2021 - Elsevier
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Role of artificial intelligence in radiogenomics for cancers in the era of precision medicine

S Saxena, B Jena, N Gupta, S Das, D Sarmah… - Cancers, 2022 - mdpi.com
Simple Summary Recently, radiogenomics has played a significant role and offered a new
understanding of cancer's biology and behavior in response to standard therapy. It also …

A survey of deep-learning applications in ultrasound: Artificial intelligence–powered ultrasound for improving clinical workflow

Z Akkus, J Cai, A Boonrod, A Zeinoddini… - Journal of the American …, 2019 - Elsevier
Ultrasound is the most commonly used imaging modality in clinical practice because it is a
nonionizing, low-cost, and portable point-of-care imaging tool that provides real-time …

Hybrid deep learning segmentation models for atherosclerotic plaque in internal carotid artery B-mode ultrasound

PK Jain, N Sharma, AA Giannopoulos, L Saba… - Computers in biology …, 2021 - Elsevier
The automated and accurate carotid plaque segmentation in B-mode ultrasound (US) is an
essential part of stroke risk stratification. Previous segmented methods used AtheroEdge™ …