One of the most important problems of modern medicine, which, in particular, precludes the effective implementation of new diagnostic methods such as population screening, is the steady increase of volumes of important medical data, as well as insufficient attention to the analysis of the dynamics of the patients’ condition. These problems can be solved by the information support of medical specialist in the process of research and in the formation of recommendations for further management of patients. In the study, we examined the possible ways of solving these problems through the development of software tools for creation of knowledge bases of recommendations for monitoring and treatment of various diseases, as well as intelligent decision support by the example of cancer. The results of tests of these solutions allow speaking about their effectiveness and applicability in clinical practice.

Oncologists nowadays are faced with big amount of heterogeneous medical data of diagnostic studies. Possible errors in determining the nature and extent of spread the tumor process will inevitably reduce the effectiveness of treatment and increase the unnecessary costs to it. To reduce the burden on clinicians, various computer-aided solutions based on machine learning algorithms are being developed. We made an attempt to evaluate effectiveness of thirteen machine learning algorithms in the tasks of classification of pathologic tissue samples in cancerous thorax based on gene expression levels. For a preliminary study we used open data set of molecular genetics composition of lung adenocarcinoma and pleural mesothelioma. Effectiveness of machine learning algorithms was evaluated by Matthews correlation coefficient and Area Under ROC Curve. Best results were showed by two methods: Bayesian logistic regression and Discriminative Multinomial Naive Bayes classifier. Nevertheless, all of the methods were effective at automatic discrimination of two types of cancer. That proves machine learning algorithms are applicable in lung cancer classification. In the future studies it will be carried out a similar analysis of the diagnostic value of methods for other malignancies with more complex differential morphological diagnosis. Similar methods can be applied to other diagnostic studies including computerized tomography image analysis in the differential diagnosis of lung nodules.

This review summarizes data dedicated to improving the efficiency of screening of malignant tumors through the use of modern information and telecommunication technologies. It is showed that currently available software solutions in the field of medical imaging is not enough adapted for population screening. So far there is no single standard that defines checking algorithms of data processing at certain controlled conditions. The most expected result will be the organization of information centralized storage, sharing diagnostic data, providing broad access to them, automated analysis and selection of diagnostically significant results through the software. The basic requirements for the development of self-learning systems for intelligent processing array of heterogeneous data through the use of technologies of semantic networks are provided.

This review article analyzes data of literature devoted to the description, interpretation and classification of focal (nodal) changes in the lungs detected by computed tomography of the chest cavity. There are discussed possible criteria for determining the most likely of their character--primary and metastatic tumor processes, inflammation, scarring, and autoimmune changes, tuberculosis and others. Identification of the most characteristic, reliable and statistically significant evidences of a variety of pathological processes in the lungs including the use of modern computer-aided detection and diagnosis of sites will optimize the diagnostic measures and ensure processing of a large volume of medical data in a short time.

The aim of the offered article is to review the state-of-the-art devices for noninvasive measurement of the cardiovascular parameters, based on the pulse wave sensors. The article describes the advantages and disadvantages of the sensors, classified according to their principle of measurement. Attention is drawn to the possibility of applying devices for longtime monitoring, also offered development of authors for this purpose.

Bio-inspired nano-communication enables nanoscale devices to exchange information with each other by various natural mechanisms of data transfer. One of the most perspective way in bio-inspired communications is using the protein interactions, which refer from various proteins conformation states. In this paper, we describe our new coarse-grained model for protein conformation estimation based on fast transport task solving, developed algorithm and software which implement this model are provided.

This publication is devoted to the personality and creative designs of uncommon American scientist, the engineer and the inventor – Norman Jefferis «Jeff» Holter. Norman Jefferis Holter introduced the terminology of «nuclear medicine» for the name of the new at that time area which associated with employment of the achievements of the nuclear physics in the medical goals. Also he is the author of ambulatory cardiological monitoring.

The purpose of this publication – to familiarize the readers with the newest achievements in the field of vision machine technologies with regard to the occlusal plethysmography. The principle of plethysmograph work is similar to a principle of mechanical occlusal plethysmograph work, with that only a difference that working measuring environment (gas or liquid) is replaced with laser labels, and fixation of change of volume is made by machine vision with the subsequent computer processing. Application of laser technologies of machine vision in future considerably simplified process of diagnostics, will allow to carry out diagnostics repeatedly and under various conditions of, for example, case of external action on the examined finiteness of the of heat, cold, physical exercise, and so, is representative of more and accurate picture of the state of blood vessels in the dynamics.

This article assesses the benefits of outpatient rapid diagnosis solutions for cardiovascular and respiratory human systems on the basis of a comparative performance analysis of existing devices for monitoring the cardiovascular and respiratory systems in everyday activities, and telemetry system for remote on-line monitoring of patients cardiorespiratory parameters developed by the authors

Diagnostics of a functional condition of an organism of athletes is based on methods of cardiological monitoring. Respiratory methods of diagnostics in sports medicine can become important addition in the prevention of development of cardiovascular diseases and need additional researches. In an assessment of a functional condition of athletes authors of article allocate a particular interest for remote methods of on-line diagnostics. In article possibilities of application of remote respiratory monitoring in functional diagnostics of athletes and the people which work is connected with raised loads of an organism are considered. Respiratory monitoring is applied to carry out microminiature accelerometers. The method of mobile cellular systems is offered for on-line monitoring.

Increase of cardiovascular tension is a common thing for professional athletic training. Cardiovascular pathologies can be prevented by permanent physiological monitoring using, among others, the methods of cardiologic monitoring so far available in stationary diagnostic centers. On-line remote diagnostics during training is potent to enhance effectiveness and efficiency of sporting people's health management. In addition, RD will also enable extensive investigations of the bodily responses of individually determined training loads. The paper gives an overview of the current RM technologies.