Probing the Neuro-psychological Changes Observed with the Administration
of COVID-19 Drugs

Chatterjee, Indranath; Bansal, Videsha

doi:10.2174/1568026623666221223112247

Cited by 2 publications

(1 citation statement)

References 85 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, studies (5,6) on the neural mechanisms underlying pain in OA patients can help us understand the disease and develop more effective treatments. Researchers may be able to develop more targeted and effective treatments for chronic pain by identifying specific brain regions and networks involved in pain processing in OA patients, including non-pharmacological interventions such as cognitive-behavioral therapy and novel pharmacological approaches (7) targeting the central nervous system. In addition, studies into the neural mechanisms underlying chronic pain in OA may have broader implications for other chronic pain conditions like fibromyalgia, chronic back pain, and neuropathic pain, which share some characteristics with OA.…”

Section: Introductionmentioning

confidence: 99%

Detection of brain regions responsible for chronic pain in osteoarthritis: an fMRI-based neuroimaging study using deep learning

2023

Self Cite

View full text Add to dashboard Cite

IntroductionChronic pain is a multifaceted condition that has yet to be fully comprehended. It is frequently linked with a range of disorders, particularly osteoarthritis (OA), which arises from the progressive deterioration of the protective cartilage that cushions the bone endings over time.MethodsIn this paper, we examine the impact of chronic pain on the brain using advanced deep learning (DL) algorithms that leverage resting-state functional magnetic resonance imaging (fMRI) data from both OA pain patients and healthy controls. Our study encompasses fMRI data from 51 pain patients and 20 healthy subjects. To differentiate chronic pain-affected OA patients from healthy controls, we introduce a DL-based computer-aided diagnosis framework that incorporates Multi-Layer Perceptron and Convolutional Neural Networks (CNN), separately.ResultsAmong the examined algorithms, we discovered that CNN outperformed the others and achieved a notable accuracy rate of nearly 85%. In addition, our investigation scrutinized the brain regions affected by chronic pain and successfully identified several regions that have not been mentioned in previous literature, including the occipital lobe, the superior frontal gyrus, the cuneus, the middle occipital gyrus, and the culmen.DiscussionThis pioneering study explores the applicability of DL algorithms in pinpointing the differentiating brain regions in OA patients who experience chronic pain. The outcomes of our research could make a significant contribution to medical research on OA pain patients and facilitate fMRI-based pain recognition, ultimately leading to enhanced clinical intervention for chronic pain patients.

show abstract

Section: Introductionmentioning

confidence: 99%