PROSPECTS OF ARTIFICIAL INTELLIGENCE IN CARRYING OUT THE ONCOLOGICAL COMPONENT OF MEDICAL EXAMINATION OF THE POPULATION

2019 ◽  
Vol 65 (2) ◽  
pp. 234-237
Author(s):  
Vyacheslav Cherenkov ◽  
A. Petrov ◽  
I. Gulkov ◽  
A. Kostyukov
Keyword(s):  
Artificial Intelligence ◽  
Early Diagnosis ◽  
Mass Screening ◽  
Malignant Tumors ◽  
Risk Groups ◽  
Modern World ◽  
Pilot Program ◽  
Urgent Problem ◽  
Gender And Age ◽  
Group Version

Diagnosis of malignant tumors is an urgent problem of the modern world. Early diagnosis depends on General practitioners. The doctor should conduct a systematic examination of the patient regularly, taking into account the risk groups, gender and age. With mass screening, signs of dysplasia or an early focus, developing cancer can «slip away» [1]. Optimization of analysis and examination algorithms is required, which is not always possible for one person. Positive application of the digital program with elements of imaging in Oncology, we were able to create such a class of tasks for the preliminary subjective-objective survey of patients in three versions: with a widescreen screen and consoles for patients (group version up to 15 or more patients), interactive (touch) and tablet. The results of the survey are sent through the accepted channels to the doctor with recommendations for further examination, and the patient is given a coupon. The pilot program showed that the system of such robotic technologies in the future can replace the oncologist in its development to artificial intelligence at the stage of the primary link.

Affective disorders as risk predictor of developing cancer on example of malignant tumors of pancreas

2020 ◽  
pp. 44-47
Author(s):  
A. V. Pavlovsky ◽  
V. E. Moiseenko ◽  
S. A. Popov ◽  
F. Sh. Gadzhieva ◽  
G. V. Rukavishnikov ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Early Diagnosis ◽  
Affective Disorders ◽  
Clinical Symptoms ◽  
Psychiatric Symptoms ◽  
Malignant Tumors ◽  
Malignant Neoplasm ◽  
Risk Groups ◽  
Scientific Debate ◽  
Risk Predictor

Pancreatic cancer is the 12th most common malignant neoplasm and the 7th most common cancer related death worldwide. Early diagnosis of pancreatic cancer is complicated, since the disease proceeds for a long time without pronounced clinical symptoms, and the identification and screening of the so-called risk groups of patients is difficult, since the etiology of pancreatic cancer is currently a matter of scientific debate. Early diagnosis of pancreatic cancer can be based on the anamnestic analysis of the psychoemotional status of patients. Back in the early 20th century, based on an analysis of the results of a survey of patients with pancreatic cancer, researchers described a triad of affective signs, including depression, anxiety and a sense of impending death, which worried patients in the early stages of development of the disease. According to literature, the psychiatric symptoms of pancreatic cancer can appear 43 months before the somatic symptoms and occur in more than 50 % of patients. To date, there are a number of concepts in the literature that point to a significant contribution of affective disorders to the development of pancreatic cancer. The aim of this review is to analyze the literature data on the relationship between affective disorders and the development of pancreatic cancer.

AI-Provided Instant Differential Diagnosis of Pemphigus Vulgaris and Bullous Pemphigoid: Qualitative Study (Preprint)

2020 ◽  
Author(s):  
Xiaoyu He ◽  
Juan Su ◽  
Guangyu Wang ◽  
Kang Zhang ◽  
Navarini Alexander ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Early Diagnosis ◽  
Image Classification ◽  
Bullous Pemphigoid ◽  
Skin Diseases ◽  
Pemphigus Vulgaris ◽  
Classification Model ◽  
Clinical Image ◽  
Clinical Images ◽  
Multimodal Classification

BACKGROUND Pemphigus vulgaris (PV) and bullous pemphigoid (BP) are two rare but severe inflammatory dermatoses. Due to the regional lack of trained dermatologists, many patients with these two diseases are misdiagnosed and therefore incorrectly treated. An artificial intelligence diagnosis framework would be highly adaptable for the early diagnosis of these two diseases. OBJECTIVE Design and evaluate an artificial intelligence diagnosis framework for PV and BP. METHODS The work was conducted on a dermatological dataset consisting of 17,735 clinical images and 346 patient metadata of bullous dermatoses. A two-stage diagnosis framework was designed, where the first stage trained a clinical image classification model to classify bullous dermatoses from five common skin diseases and normal skin and the second stage developed a multimodal classification model of clinical images and patient metadata to further differentiate PV and BP. RESULTS The clinical image classification model and the multimodal classification model achieved an area under the receiver operating characteristic curve (AUROC) of 0.998 and 0.942, respectively. On the independent test set of 20 PV and 20 BP cases, our multimodal classification model (sensitivity: 0.85, specificity: 0.95) performed better than the average of 27 junior dermatologists (sensitivity: 0.68, specificity: 0.78) and comparable to the average of 69 senior dermatologists (sensitivity: 0.80, specificity: 0.87). CONCLUSIONS Our diagnosis framework based on clinical images and patient metadata achieved expert-level identification of PV and BP, and is potential to be an effective tool for dermatologists in remote areas in the early diagnosis of these two diseases.

scholarly journals Epidemiological factors associated with recent HIV infection among newly-diagnosed cases in Singapore, 2013–2017

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li Wei Ang ◽  
Carmen Low ◽  
Chen Seong Wong ◽  
Irving Charles Boudville ◽  
Matthias Paul Han Sim Toh ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Hiv Infection ◽  
Hiv Transmission ◽  
Risk Groups ◽  
Newly Diagnosed ◽  
Hiv Diagnosis ◽  
Factors Associated ◽  
Epidemiological Factors ◽  
Voluntary Testing ◽  
Recent Hiv Infection

AbstractBackgroundEarly diagnosis is crucial in securing optimal outcomes in the HIV care cascade. Recent HIV infection (RHI) serves as an indicator of early detection in the course of HIV infection. Surveillance of RHI is important in uncovering at-risk groups in which HIV transmission is ongoing. The study objectives are to estimate the proportion of RHI among persons newly-diagnosed in 2013–2017, and to elucidate epidemiological factors associated with RHI in Singapore.MethodsAs part of the National HIV Molecular Surveillance Programme, residual plasma samples of treatment-naïve HIV-1 positive individuals were tested using the biotinylated peptide-capture enzyme immunoassay with a cutoff of normalized optical density ≤ 0.8 for evidence of RHI. A recent infection testing algorithm was applied for the classification of RHI. We identified risk factors associated with RHI using logistic regression analyses.ResultsA total of 701 newly-diagnosed HIV-infected persons were included in the study. The median age at HIV diagnosis was 38 years (interquartile range, 28–51). The majority were men (94.2%), and sexual route was the predominant mode of HIV transmission (98.3%). Overall, 133/701 (19.0, 95% confidence interval [CI] 16.2–22.0%) were classified as RHI. The proportions of RHI in 2015 (31.1%) and 2017 (31.0%) were significantly higher than in 2014 (11.2%). A significantly higher proportion of men having sex with men (23.4, 95% CI 19.6–27.6%) had RHI compared with heterosexual men (11.1, 95% CI 7.6–15.9%). Independent factors associated with RHI were: age 15–24 years (adjusted odds ratio [aOR] 4.18, 95% CI 1.69–10.31) compared with ≥55 years; HIV diagnosis in 2015 (aOR 2.36, 95% CI 1.25–4.46) and 2017 (aOR 2.52, 95% CI 1.32–4.80) compared with 2013–2014; detection via voluntary testing (aOR 1.91, 95% CI 1.07–3.43) compared with medical care; and self-reported history of HIV test(s) prior to diagnosis (aOR 1.72, 95% CI 1.06–2.81).ConclusionAlthough there appears to be an increasing trend towards early diagnosis, persons with RHI remain a minority in Singapore. The strong associations observed between modifiable behaviors (voluntary testing and HIV testing history) and RHI highlight the importance of increasing the accessibility to HIV testing for at-risk groups.

ARTIFICIAL INTELLIGENCE

2021 ◽  
pp. 56-63
Author(s):  
V. I. Matveev
Keyword(s):  
Artificial Intelligence ◽  
Social Environment ◽  
Science And Technology ◽  
Main Direction ◽  
Modern World ◽  
The Social ◽  
Legislative Measures

Artificial intelligence is becoming the main direction of the development of science and technology, making progress at a new level. Automation of production, the implementation of operations in hazardous and harmful areas, the implementation of routine actions in the environment are inevitable in the modern world. A person creates an analogue for himself, realizing the possible consequences and limiting them to legislative acts. The article provides positive examples of the implementation of the artificial intelligence project and legislative measures that limit its impact on the social environment.

scholarly journals Gender and Age Stratified Analyses of Nutrient and Dietary Pattern Associations with Circulating Lipid Levels Identify Novel Gender and Age-Specific Correlations

Nutrients ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1760 ◽  
Author(s):  
Huifeng Jin ◽  
Jessie Nicodemus-Johnson
Keyword(s):  
Fatty Acid ◽  
Dietary Pattern ◽  
Dietary Habits ◽  
Density Lipoprotein ◽  
Hdl Cholesterol ◽  
Nutrient Level ◽  
Modern World ◽  
Lipid Levels ◽  
Gender And Age ◽  
Gender Specific

Dyslipidemia is a precursor to a myriad of cardiovascular diseases in the modern world. Age, gender, and diet are known modifiers of lipid levels, however they are not frequently investigated in subset analyses. Food and nutrient intakes from National Health and Nutrition Examination Study 2001–2013 were used to assess the correlation between lipid levels (high-density lipoprotein (HDL) cholesterol, triglycerides (TG), low-density lipoprotein (LDL) cholesterol, and total cholesterol (TC):HDL cholesterol ratio) and nutritional intake using linear regression. Associations were initially stratified by gender and significant gender correlations were further stratified by age. Analyses were performed at both the dietary pattern and nutrient level. Dietary pattern and fat intake correlations agreed with the literature in direction and did not demonstrate gender or age effects; however, we observed gender and age interactions among other dietary patterns and individual nutrients. These effects were independent of ethnicity, caloric intake, socioeconomic status, and physical activity. Elevated HDL cholesterol levels correlated with increasing vitamin and mineral intake in females of child bearing age but not males or older females (≥65 years). Moreover, increases in magnesium and retinol intake correlated with HDL cholesterol improvement only in females (all age groups) and males (35–64), respectively. Finally, a large amount of gender-specific variation was associated with TG levels. Females demonstrated positive associations with sugar and carbohydrate while males show inverse associations with polyunsaturated fatty acid (PUFA) intake. The female-specific association increased with the ratio of carbohydrate: saturated fatty acid (SFA) intake, suggesting that gender specific dietary habits may underlie the observed TG-nutrient correlations. Our study provides evidence that a subset of previously established nutrient-lipid associations may be gender or age-specific. Such discoveries provide potential new avenues for further research into personalized nutritional approaches to treat dyslipidemia.

scholarly journals Prospective selected biomarkers in COVID-19 diagnosis and treatment

2021 ◽  
Author(s):  
Tahani Tabassum ◽  
Ahsab Rahman ◽  
Yusha Araf ◽  
Md A Ullah ◽  
Mohammad J Hosen
Keyword(s):  
Early Diagnosis ◽  
Risk Groups ◽  
Viral Pathogenesis ◽  
Health Concern ◽  
Effective Strategy ◽  
Proper Treatment ◽  
Pulmonary Infections ◽  
Disease Prognosis ◽  
Proper Diagnosis

COVID-19 has become a global health concern, due to the high transmissible nature of its causal agent and lack of proper treatment. Early diagnosis and nonspecific medical supports of the patients appeared to be effective strategy so far to combat the pandemic caused by COVID-19 outbreak. Biomarkers can play pivotal roles in timely and proper diagnosis of COVID-19 patients, as well as for distinguishing them from other pulmonary infections. Besides, biomarkers can help in reducing the rate of mortality and evaluating viral pathogenesis with disease prognosis. This article intends to provide a broader overview of the roles and uses of different biomarkers in the early diagnosis of COVID-19, as well as in the classification of COVID-19 patients into multiple risk groups.

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