scholarly journals On modern methods of automated diagnosis of skin tumors in clinical practice

2020 ◽  
pp. 76-78
Author(s):  
V. Yu. Sergeev ◽  
Yu. Yu. Sergeev ◽  
O. B. Tamrazova ◽  
V. G. Nikitaev ◽  
A. N. Pronichev
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Clinical Practice ◽  
Public Health Service ◽  
Automated Diagnosis ◽  
Skin Cancers ◽  
Modern Methods ◽  
Number Of Publications ◽  
New Algorithms ◽  
Artificial Intelligence Systems

Despite the existence of many algorithms for automated diagnosis of melanoma and other skin cancers, these remain almost inaccessible to public health service. A small number of publications on the efficacy of existing artificial intelligence systems marks the problems of their implementation into current examination routines in dermatology and oncology. New algorithms and software solutions as well as studies demonstrating their diagnostic accuracy on compatible and verifiable clinical material are still in demand.

scholarly journals Artificial Intelligence in Public Health Dentistry

2021 ◽  
Vol 5 (9) ◽  
pp. RV1-RV5
Author(s):  
Sahrish Tariq ◽  
Nidhi Gupta ◽  
Preety Gupta ◽  
Aditi Sharma
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Neural Networks ◽  
Clinical Practice ◽  
Correct Diagnosis ◽  
Scientific Research ◽  
Modern Science ◽  
Appropriate Technology ◽  
Human Element ◽  
New Knowledge

The educational needs must drive the development of the appropriate technology”. They should not be viewed as toys for enthusiasts. Nevertheless, the human element must never be dismissed. Scientific research will continue to offer exciting technologies and effective treatments. For the profession and the patients, it serves to benefit fully from modern science, new knowledge and technologies must be incorporated into the mainstream of dental education. The technologies of modern science have astonished and intrigued our imagination. Correct diagnosis is the key to a successful clinical practice. In this regard, adequately trained neural networks can be a boon to diagnosticians, especially in conditions having multifactorial etiology.

scholarly journals Blockchain in Healthcare: Insights on COVID-19

2020 ◽  
Vol 17 (19) ◽  
pp. 7167 ◽  
Author(s):  
Antonio Fusco ◽  
Grazia Dicuonzo ◽  
Vittorio Dell’Atti ◽  
Marco Tatullo
Keyword(s):  
Artificial Intelligence ◽  
Risk Management ◽  
Clinical Practice ◽  
Swot Analysis ◽  
Healthcare Management ◽  
Evidence Based ◽  
Clinical Workflow ◽  
Strategic Role ◽  
Digital Healthcare ◽  
Artificial Intelligence Systems

The SARS-CoV2 pandemic has impacted risk management globally. Blockchain has been increasingly applied to healthcare management, as a strategic tool to strengthen operative protocols and to create the proper basis for an efficient and effective evidence-based decisional process. We aim to validate blockchain in healthcare, and to suggest a trace-route for a COVID19-safe clinical practice. The use of blockchain in combination with artificial intelligence systems allows the creation of a generalizable predictive system that could contribute to the containment of pandemic risk on national territory. A SWOT analysis of the adoption of a blockchain-based prediction model in healthcare and SARS-CoV-2 infection has been carried out to underline opportunities and limits to its adoption. Blockchain could play a strategic role in future digital healthcare: specifically, it may work to improve COVID19-safe clinical practice. The main concepts, and particularly those related to clinical workflow, obtainable from different blockchain-based models have been reported here and critically discussed.

Management algorithms and artificial intelligence systems for cardiopulmonary bypass

Perfusion ◽  
2021 ◽  
pp. 026765912110307
Author(s):  
Ignazio Condello ◽  
Giuseppe Santarpino ◽  
Giuseppe Nasso ◽  
Marco Moscarelli ◽  
Flavio Fiore ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Clinical Practice ◽  
Cardiopulmonary Bypass ◽  
Human Error ◽  
Metabolic Parameters ◽  
Monitoring Systems ◽  
Metabolic Monitoring ◽  
Metabolic Management ◽  
Management Algorithms ◽  
Artificial Intelligence Systems

This article introduces management algorithms to support operators in choosing the best strategy for metabolic management during cardiopulmonary bypass using artificial intelligence systems. We developed algorithms for the identification of the optimal way for assessing metabolic parameters. Different management algorithms for extracorporeal procedures interfaced with metabolic monitoring systems already exist on the market and are applied in clinical practice. These algorithms could provide guidance for selecting the best metabolic strategy with the aim at reducing human error and optimizing management.

A Clinical Practice Guideline for Treating Tobacco Use and Dependence: A US Public Health Service Report

JAMA ◽  
2000 ◽  
Vol 283 (24) ◽  
pp. 3244-3254 ◽  
Author(s):  
The Tobacco Use and Dependence Clinical Practice Guideline Panel, Staff, and Consortium Representatives
Keyword(s):  
Public Health ◽  
Clinical Practice ◽  
Health Service ◽  
Tobacco Use ◽  
Clinical Practice Guideline ◽  
Practice Guideline ◽  
Public Health Service

Reducing Pulmonary Disease: The Pharmacist’s Role in Smoking Cessation

2001 ◽  
Vol 14 (2) ◽  
pp. 143-159 ◽  
Author(s):  
Karen Suchanek Hudmon ◽  
Robin L. Corelli ◽  
Lisa A. Kroon ◽  
Marilyn Standifer Shreve ◽  
Alexander V. Prokhorov
Keyword(s):  
Public Health ◽  
Smoking Cessation ◽  
Clinical Practice ◽  
Health Service ◽  
Clinical Practice Guideline ◽  
Practice Guideline ◽  
Public Health Service ◽  
Smoking Cessation Counseling ◽  
Quitting Smoking ◽  
The U.S

As an important interface with the healthcare system for many patients, pharmacists are in a unique position to assist patients with quitting smoking, thereby improving patients’ pulmonary health. Because nicotine replacement therapy products and bupropion are available to patients largely via pharmacies, the pharmacist has become a logical candidate for providing smoking cessation assistance. Furthermore, research has shown that when pharmacists counsel patients on medications for quitting smoking, their intervention positively impacts smoking cessation rates. This article provides a review of methods for cessation and provides pharmacists with feasible and effective smoking cessation counseling strategies for implementation into everyday practice. The intervention approach draws heavily upon the U.S. Public Health Service Clinical Practice Guideline for Treating Tobacco Use and Dependence.

scholarly journals Diagnostic performance study on the melanoma automated diagnosis software powered by artificial intelligence technologies

2020 ◽  
Vol 23 (5) ◽  
pp. 288-292
Author(s):  
Vasiliy Yu. Sergeev ◽  
Yu. Yu. Sergeev ◽  
O. B. Tamrazova ◽  
V. G. Nikitaev ◽  
A. N. Pronichev ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Diagnostic Performance ◽  
High Sensitivity ◽  
Skin Neoplasms ◽  
Skin Tumors ◽  
Published Data ◽  
Performance Study ◽  
Automated Diagnosis ◽  
Accuracy Rate ◽  
Artificial Intelligence Systems

INTRODUCTION: The research evaluates a series of publications on the machine recognition efficacy of cutaneous melanoma dermatoscopic images. Some authors report high sensitivity and specificity of automated diagnostics of skin tumors. Significant differences in the published data can be attributed to the use of different algorithms and groups of skin neoplasms to calculate the accuracy rate. MATERIALS AND METHODS: The diagnostic performance of two automated artificial intelligence systems is compared. RESULTS: The convolutional neural network algorithm improves the overall diagnostic accuracy by 7% compared to the algorithm without deep learning, while the overall accuracy rate was 78%. An initial set of 100 dermatoscopic images used in the study is published online for the assessment of the applicability of the obtained data when introducing existing artificial intelligence systems. CONCLUSION: The main limitations and possible ways to further improve the automated diagnosis of skin tumors based on digital dermatoscopy are outlined.

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