A Concept of Smart Medical Autonomous Distributed System for Diagnostics Based on Machine Learning Technology

Velichko, Elena; Nepomnyashchaya, Elina; Baranov, Maksim; Galeeva, Marina; Pavlov, V. I.; Zavjalov, Sergey V.; Savchenko, Ekaterina; Pervunina, Tatiana; Govorov, Igor; Комличенко, Э. В.

doi:10.1007/978-3-030-30859-9_44

Cited by 11 publications

(3 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The preliminary results obtained for assessing the concentration of indocyanine green in various liquids can be the basis for further studies [ 21 ]. This development can be included in the smart medical autonomous distributed system for diagnostics based on machine learning technology [ 22 ].…”

Section: Resultsmentioning

confidence: 99%

Design of Liver Functional Reserve Estimation Technique Based on Optical Densitometry

et al. 2020

Self Cite

View full text Add to dashboard Cite

This work is aimed at creating a modified invasive technique for assessing the liver’s functional reserves. A study of the degree of hepatodepression is carried out by measuring the plasma elimination of indocyanine green using the method of optical densitometry. This paper presents test results for an aqueous solution and an albumin solution, as well as the results of measurements of plasma elimination of indocyanine green for patients with liver disease. Perfecting the proposed method will make an important scientific contribution to modern diagnostic medicine. Diagnosing the stages in the progression of the disease and its developing complications can make it possible to rapidly correct the patient’s treatment algorithm, achieving positive outcomes in medical practice.

show abstract

Section: Resultsmentioning

confidence: 99%

Design of Liver Functional Reserve Estimation Technique Based on Optical Densitometry

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…This type of system can be improved to a smart medical autonomous distributed system for diagnostics based on machine leaning technology [ 41 ]. This concept presupposes the construction of several data centers.…”

Section: Discussionmentioning

confidence: 99%

Simplified Convolutional Neural Network Application for Cervix Type Classification via Colposcopic Images

et al. 2022

Self Cite

View full text Add to dashboard Cite

The inner parts of the human body are usually inspected endoscopically using special equipment. For instance, each part of the female reproductive system can be examined endoscopically (laparoscopy, hysteroscopy, and colposcopy). The primary purpose of colposcopy is the early detection of malignant lesions of the cervix. Cervical cancer (CC) is one of the most common cancers in women worldwide, especially in middle- and low-income countries. Therefore, there is a growing demand for approaches that aim to detect precancerous lesions, ideally without quality loss. Despite its high efficiency, this method has some disadvantages, including subjectivity and pronounced dependence on the operator’s experience. The objective of the current work is to propose an alternative to overcoming these limitations by utilizing the neural network approach. The classifier is trained to recognize and classify lesions. The classifier has a high recognition accuracy and a low computational complexity. The classification accuracies for the classes normal, LSIL, HSIL, and suspicious for invasion were 95.46%, 79.78%, 94.16%, and 97.09%, respectively. We argue that the proposed architecture is simpler than those discussed in other articles due to the use of the global averaging level of the pool. Therefore, the classifier can be implemented on low-power computing platforms at a reasonable cost.

show abstract

“…Currently, new technologies are being developed for people with mental disorders, including artificial intelligence (AI) that already plays a major role in general medicine and research [42][43][44]. Techniques based on AI are widely applied in medical imaging diagnostics [45][46][47], but they can also be used for personalization purposes [48][49][50]. By identifying patterns in the types of interactions linked to specific types of disorders, these techniques could help individualize interventions provided by moderators of web-based forums.…”

Section: Introductionmentioning

confidence: 99%

Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions

Storman¹,

Jemioło²,

Świerz³

et al. 2022

JMIR Ment Health

View full text Add to dashboard Cite

Background An increasing number of online support groups are providing advice and information on topics related to mental health. Objective This study aimed to investigate the needs that internet users meet through peer-to-peer interactions. Methods A search of 4 databases was performed until August 15, 2022. Qualitative or mixed methods (ie, qualitative and quantitative) studies investigating interactions among internet users with mental disorders were included. The φ coefficient was used and machine learning techniques were applied to investigate the associations between the type of mental disorders and web-based interactions linked to seeking help or support. Results Of the 13,098 identified records, 44 studies (analyzed in 54 study-disorder pairs) that assessed 82,091 users and 293,103 posts were included. The most frequent interactions were noted for people with eating disorders (14/54, 26%), depression (12/54, 22%), and psychoactive substance use disorders (9/54, 17%). We grouped interactions between users into 42 codes, with the empathy or compassion code being the most common (41/54, 76%). The most frequently coexisting codes were request for information and network (35 times; φ=0.5; P<.001). The algorithms that provided the best accuracy in classifying disorders by interactions were decision trees (44/54, 81%) and logistic regression (40/54, 74%). The included studies were of moderate quality. Conclusions People with mental disorders mostly use the internet to seek support, find answers to their questions, and chat. The results of this analysis should be interpreted as a proof of concept. More data on web-based interactions among these people might help apply machine learning methods to develop a tool that might facilitate screening or even support mental health assessment.

show abstract

A Concept of Smart Medical Autonomous Distributed System for Diagnostics Based on Machine Learning Technology

Cited by 11 publications

References 37 publications

Design of Liver Functional Reserve Estimation Technique Based on Optical Densitometry

Design of Liver Functional Reserve Estimation Technique Based on Optical Densitometry

Simplified Convolutional Neural Network Application for Cervix Type Classification via Colposcopic Images

Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions

Contact Info

Product

Resources

About