[The application of artificial intellect in health care: prospects and challenges for science and clinical medicine].

The paper analyses publications data related to issues of application of AI and machine learning systems in medical science and practice. The particular attention is paid to key points of AI application in health care: diagnostics, telemedicine, development of new medications, medical rehabilitation and management decision-making process. Despite broad perspectives of applying the given systems in clinical practice and pharmaceutical industry, there are a number of such unsolved problems as ensuring information security, risk of making erroneous decisions and necessity to change existing normative legal base of health care.

Institutional Training Opportunities for PhD Students in Laboratory Medicine: An Unmet Career Development Need?

In the United States, the credentialing of PhD-scientists as medical directors of clinical laboratories is driven by formal postdoctoral training programs. Prior to acceptance in one these accredited fellowships, however, a trainee's exposure to the field can be far less standardized, with significant ramifications for their awareness and competitiveness. In the current article, we describe our recent experiences in developing local, institution-based immersion opportunities for PhD experiences in the subdisciplines of laboratory medicine (clinical microbiology, clinical chemistry, and molecular genetics/genomics). It is our hope that this article-and a corresponding online survey-can prompt reflection and discussion on the status of early career training opportunities in these key clinical areas.

The impact of machine learning on patient care: A systematic review.

BACKGROUND: Despite the expanding use of machine learning (ML) in fields such as finance and marketing, its application in the daily practice of clinical medicine is almost non-existent. In this systematic review, we describe the various areas within clinical medicine that have applied the use of ML to improve patient care. METHODS: A systematic review was performed in accordance with the PRISMA guidelines using Medline(R), EBM Reviews, Embase, Psych Info, and Cochrane Databases, focusing on human studies that used ML to directly address a clinical problem. Included studies were published from January 1, 2000 to May 1, 2018 and provided metrics on the performance of the utilized ML tool. RESULTS: A total of 1909 unique publications were reviewed, with 378 retrospective articles and 8 prospective articles meeting inclusion criteria. Retrospective publications were found to be increasing in frequency, with 61 % of articles published within the last 4 years. Prospective articles comprised only 2 % of the articles meeting our inclusion criteria. These studies utilized a prospective cohort design with an average sample size of 531. CONCLUSION: The majority of literature describing the use of ML in clinical medicine is retrospective in nature and often outlines proof-of-concept approaches to impact patient care. We postulate that identifying and overcoming key translational barriers, including real-time access to clinical data, data security, physician approval of "black box" generated results, and performance evaluation will allow for a fundamental shift in medical practice, where specialized tools will aid the healthcare team in providing better patient care.

ESCMID white paper: a guide on ESCMID guidance documents.

BACKGROUND AND AIM: The European Society of Clinical Microbiology and Infectious Diseases (ESCMID) aims to further develop its role in international medical and scientific guidance in the field of Clinical Microbiology and Infectious Diseases, where many types of guidance documents exist. The ESCMID Executive Committee and the Clinical Microbiology and Infection (CMI) editorial board wish to clarify the terminology and format to be used in ESCMID guidance documents submitted for publication in CMI, and to highlight the principles behind ESCMID guidance documents. TYPES OF GUIDANCE DOCUMENTS: There are five types of ESCMID guidance documents: White Papers, Clinical Practice Guidelines, Consensus Statements, State-of-the-Science Statements, and Position Papers. They differ in scope, methods of development, drafting group composition and preferred publication format. Guidance documents can be proposed, developed and published by ESCMID Study Groups, Committees and individual members; often, other scientific societies are involved. The full disclosure of potential conflicts of interest of all drafting group members is a requirement. FINAL REMARKS: Guidance documents constitute a common cultural and scientific background to people in the same and related professions. Also, they are an important educational and training tool. Developing a guidance document is a scientific endeavour, where a sound and transparent development process is needed, requiring multidisciplinary and personal skills.

Navigating complexity in team-based clinical settings.

CONTEXT: Educators must prepare learners to navigate the complexities of clinical care. Training programmes have, however, traditionally prioritised teaching around the biomedical and the technical, not the socio-relational or systems issues that create complexity. If we are to transform medical education to meet the demands of 21st century practice, we need to understand how clinicians perceive and respond to complex situations. METHODS: Constructivist grounded theory informed data collection and analysis; during semi-structured interviews, we used rich pictures to elicit team members' perspectives about clinical complexity in neurology and in the intensive care unit. We identified themes through constant comparative analysis. RESULTS: Routine care became complex when the prognosis was unknown, when treatment was either non-existent or had been exhausted or when being patient and family centred challenged a system's capabilities, or participants' training or professional scope of practice. When faced with complexity, participants reported that care shifted from relying on medical expertise to engaging in advocacy. Some physician participants, however, either did not recognise their care as advocacy or perceived it as outside their scope of practice. In turn, advocacy was often delegated to others. CONCLUSIONS: Our research illuminates how expert clinicians manoeuvre moments of complexity; specifically, navigating complexity may rely on mastering health advocacy. Our results suggest that advocacy is often negotiated or collectively enacted in team settings, often with input from patients and families. In order to prepare learners to navigate complexity, we suggest that programmes situate advocacy training in complex clinical encounters, encourage reflection and engage non-physician team members in advocacy training.

Developing a complex systems perspective for medical education to facilitate the integration of basic science and clinical medicine.

RATIONALE, AIMS AND OBJECTIVES: The purpose of medical education is to produce competent and capable professional practitioners who can combine the art and science of medicine. Moreover, this process must prepare individuals to practise in a field in which knowledge is increasing and the contexts in which that knowledge is applied are changing in unpredictable ways. The 'basic sciences' are important in the training of a physician. The goal of basic science training is to learn it in a way that the material can be applied in practice. Much effort has been expended to integrate basic science and clinical training, while adding many other topics to the medical curriculum. This effort has been challenging. The aims of the paper are (1) to propose a unifying conceptual framework that facilitates knowledge integration among all levels of living systems from cell to society and (2) illustrate the organizing principles with two examples of the framework in action - cybernetic systems (with feedback) and distributed robustness. METHODS: Literature related to hierarchical and holarchical frameworks was reviewed. RESULTS: An organizing framework derived from living systems theory and spanning the range from molecular biology to health systems management was developed. The application of cybernetic systems to three levels (regulation of pancreatic beta cell production of insulin, physician adjustment of medication for glycaemic control and development and action of performance measures for diabetes care) was illustrated. Similarly distributed robustness was illustrated by the DNA damage response system and principles underlying patient safety. CONCLUSIONS: Each of the illustrated organizing principles offers a means to facilitate the weaving of basic science and clinical medicine throughout the course of study. The use of such an approach may promote systems thinking, which is a core competency for effective and capable medical practice.

[FOUNDER PERM PROVINCIAL MEDICINE--"PEOPLE'S DOCTOR" F. H. GRAIL].

The article presents the biography of one wonderful doctors, who have high human, civil and professional qualities, Fyodor Ch. Gral.