Raman Microspectroscopy of Cells and Tissue in Medical Diagnostics

2015 ◽  
pp. 339-362
Keyword(s):  
Medical Diagnostics ◽  
Raman Microspectroscopy

Polarization measurements in raman microspectroscopy.

1989 ◽  
Vol 86 ◽  
pp. 1245-1251 ◽  
Author(s):  
Claude Bremard ◽  
Jacky Laureyns ◽  
George Turrell
Keyword(s):  
Raman Microspectroscopy ◽  
Polarization Measurements

Methods for Processing and Recording Biosignals for Medical Diagnostics

Vestnik MEI ◽  
2018 ◽  
Vol 5 (5) ◽  
pp. 128-138
Author(s):  
Mikhail N. Kramm ◽  
◽  
Galina V. Zhikhareva ◽  
Sergey A. Zhgoon ◽  
Nikolay О. Strelkov ◽  
...  
Keyword(s):  
Medical Diagnostics

Feature selection of the armature winding broken coils in synchronous motor using genetic algorithm and mahalanobis distance

2012 ◽  
Vol 57 (3) ◽  
pp. 829-835 ◽  
Author(s):  
Z. Głowacz ◽  
J. Kozik
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Mahalanobis Distance ◽  
Distance Measure ◽  
Synchronous Motor ◽  
Medical Diagnostics ◽  
Motor Current ◽  
Feature Spaces ◽  
Multidimensional Feature Spaces ◽  
Selection Of

The paper describes a procedure for automatic selection of symptoms accompanying the break in the synchronous motor armature winding coils. This procedure, called the feature selection, leads to choosing from a full set of features describing the problem, such a subset that would allow the best distinguishing between healthy and damaged states. As the features the spectra components amplitudes of the motor current signals were used. The full spectra of current signals are considered as the multidimensional feature spaces and their subspaces are tested. Particular subspaces are chosen with the aid of genetic algorithm and their goodness is tested using Mahalanobis distance measure. The algorithm searches for such a subspaces for which this distance is the greatest. The algorithm is very efficient and, as it was confirmed by research, leads to good results. The proposed technique is successfully applied in many other fields of science and technology, including medical diagnostics.

GEOMETRIC VISUALIZATION OF THE PROBLEM OF MEDICAL DIAGNOSTICS BIOMETRIC DATA OF THE BIOSENSOR PLATFORM

2018 ◽  
Vol 41 (4) ◽  
pp. 37-39 ◽  
Author(s):  
Igor I. Koltunov ◽  
Anton V. Panfilov ◽  
Ivan A. Poselsky ◽  
Nikolay N. Chubukov ◽  
Ivan V. Krechetov ◽  
...  
Keyword(s):  
Medical Diagnostics ◽  
Biometric Data

Recent Advances of Individual BODIPY and BODIPY-Based Functional Materials in Medical Diagnostics and Treatment

2017 ◽  
Vol 24 (25) ◽  
Author(s):  
Yuriy S. Marfin ◽  
Alexey V. Solomonov ◽  
Alexander S. Timin ◽  
Evgeniy V. Rumyantsev
Keyword(s):  
Functional Materials ◽  
Medical Diagnostics ◽  
Recent Advances

Oxonol dyes

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Heinz Mustroph
Keyword(s):  
Silver Halide ◽  
Medical Diagnostics ◽  
Water Soluble ◽  
Eukaryotic Cells ◽  
Polymethine Dyes ◽  
Technical Application ◽  
Structural Types ◽  
Oxonol Dyes ◽  
Oxygen Atoms

Abstract Oxonol dyes are classified as anionic polymethine dyes, which cover a wide variety of structural types. The name of the class originates from the oxygen atoms which terminate each end of the polymethine chains that form the backbone of their structure. In technically useful dyes, these oxygen atoms tend to be substituents of heterocycles. The main technical application of water soluble oxonol dyes was in silver halide photography as filter dyes and antihalation dyes. Lipophilic oxonol dyes are used in bio-analysis and medical diagnostics to stain cells, bacteria or liposomes for example. Their main bioanalytical usage is in the determination of membrane potentials in eukaryotic cells and prokaryotic bacteria.

A moral analysis of intelligent decision-support systems in diagnostics through the lens of Luciano Floridi’s information ethics

Human Affairs ◽  
2021 ◽  
Vol 31 (2) ◽  
pp. 149-164
Author(s):  
Dmytro Mykhailov
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Medical Diagnosis ◽  
Moral Agency ◽  
Moral Agent ◽  
Well Being ◽  
Medical Diagnostics ◽  
Intelligent Decision ◽  
Luciano Floridi ◽  
Intelligent Decision Support

Abstract Contemporary medical diagnostics has a dynamic moral landscape, which includes a variety of agents, factors, and components. A significant part of this landscape is composed of information technologies that play a vital role in doctors’ decision-making. This paper focuses on the so-called Intelligent Decision-Support System that is widely implemented in the domain of contemporary medical diagnosis. The purpose of this article is twofold. First, I will show that the IDSS may be considered a moral agent in the practice of medicine today. To develop this idea I will introduce the approach to artificial agency provided by Luciano Floridi. Simultaneously, I will situate this approach in the context of contemporary discussions regarding the nature of artificial agency. It is argued here that the IDSS possesses a specific sort of agency, includes several agent features (e.g. autonomy, interactivity, adaptability), and hence, performs an autonomous behavior, which may have a substantial moral impact on the patient’s well-being. It follows that, through the technology of artificial neural networks combined with ‘deep learning’ mechanisms, the IDSS tool achieves a specific sort of independence (autonomy) and may possess a certain type of moral agency. Second, I will provide a conceptual framework for the ethical evaluation of the moral impact that the IDSS may have on the doctor’s decision-making and, consequently, on the patient’s wellbeing. This framework is the Object-Oriented Model of Moral Action developed by Luciano Floridi. Although this model appears in many contemporary discussions in the field of information and computer ethics, it has not yet been applied to the medical domain. This paper addresses this gap and seeks to reveal the hidden potentialities of the OOP model for the field of medical diagnosis.

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