Machine Learning Based Genetic Decision Making Methodology Using Genotype-Phenotype Mapping

A methodology titled "Dynamic Selection of Essential Similar Principal Components" is presented in this study. This methodology evaluates the similarities while omitting the differences among features to accommodate for all possible similarities caused by genes. It has been tested on real data set collected from the dysmorphic facial images published in scholarly journals, thus accounting decent diagnostic information about the syndrome. The methodology has been tested with 15 different syndromes that accommodate 5 examples per syndrome. It can be concluded based on the results that a great number of syndromes indicating a characteristic pattern of facial anomalies can be typically diagnosed by employing the approach we propose in this study

Diagnostic Decision Support System in Genetic Diseases: The FaceGP DDSS

A great number of genetic disorders indicating a characteristic pattern of facial anomalies can be typically identified by analysing specific features with the aid of facial image processing methods. This study proposes a novel computer-assisted and cost-effective method by merging several methods in the characterization of the facial dysmorphology, in particular a method relying primary on face image capture and manipulation to diagnose genetic diseases

Clinical and demographic characteristics of children with familial mediterranean fever in Central Anatolia

PubMe

A validation of diagnostic score for molecular analysis of hereditary autoinflammatory syndromes with periodic fever in Turkish children

PubMe

Examining the Ethical Dilemmas in Terminating the Pregnancy Through the Basic Ethical Principles

Termination of pregnancy is an event that takes place at the request of expectant parents or due to reasons beyond their desire. However, in the presence of appropriate indications, there is no need for abortion debate. In this case, it is important to terminate the pregnancy with the request of expectant parents. Even if cessation of the pregnancy is performed within a legal framework, basic ethical principles, such as autonomy, do no harm, being useful and fairness should be applied. Precisely the problem for physicians already emerges at this point and the physicians can fall in a dilemma about how to behave with the mother or the fetus. In this article, ethical dilemmas that may arise in termination of pregnancy will be discussed briefly in accordance with the basic ethical principles

Establishment of Diagnostic Decision Support Systems (DDSS) to Prediagnose the Dysmorphic Diseases (Congenital Malformation) Efficiently Caused by Genetic Syndromes

There are specific properties, especially for facial dysmorphology caused by genetic syndromes and these properties are used by geneticists to prediagnose even before a clinical examination and genotyping are undertaken. Analyzing of properties in faces is sometimes sufficient to diagnose, however, sometimes it is necessary to analyze other specific properties of the body such as the structure of the skeleton and the characteristics of speech produced. Diagnosing of a congenital malformation correctly among many syndromes is beyond the capability of human. It will be possible to diagnose a good number of syndromes correctly by using face recognition DSS. Face recognition has attracted great attention for ten years as one of the most popular examination areas of computer vision and one of the most successful implementations of image processing. There is a need to make more efficient and effective preliminary diagnosing of syndromes by establishing novel DDSS such as novel face recognition algorithms

Establishment of a Diagnostic Decision Support System in Genetic Dysmorphology

In the clinical diagnosis of facial dysmorphology, geneticists attempt to identify the underlying syndromes by associating facial features before cyto or molecular techniques are explored. Specifying genotype-phenotype correlations correctly among many syndromes is labor intensive especially for very rare diseases. The use of a computer based prediagnosis system can offer effective decision support particularly when only very few previous examples exist or in a remote environment where expert knowledge is not readily accessible. In this work we develop and demonstrate that accurate classification of dysmorphic faces is feasible by image processing of two dimensional face images. We test the proposed system on real patient image data by constructing a dataset of dysmorphic faces published in scholarly journals, hence having accurate diagnostic information about the syndrome. Our statistical methodology represents facial image data in terms of principal component analysis (PCA) and a leave one out evaluation scheme to quantify accuracy. The methodology has been tested with 15 syndromes including 75 cases, 5 examples per syndrome. A diagnosis success rate of 79% has been established. It can be concluded that a great number of syndromes indicating a characteristic pattern of facial anomalies can be typically diagnosed by employing computer-assisted machine learning algorithms since a face develops under the influence of many genes, particularly the genes causing syndromes

Novel mutations in prenatal diagnosis of primary microcephaly.

CommentLetterFLWINinfo:eu-repo/semantics/publishe

Establishment of Diagnostic Decision Support System (DDSS) in Clinical Diagnosis of Genetic Diseases: The FaceGP DDSS Methodology and Its Applications

A face develops under the influence of many genes. Thus, facial appearance can be a significant clue in the initial identification of genetic anomalies associated with especially cognitive impairments. It may be possible to diagnose a good number of syndromes correctly by using computer-assisted face analysis. For dysmorphic syndromes -with - known genetic causes, cyto- and/or molecular genetic analysis is the appropriate route of investigation in order to confirm a diagnosis. In this study, in terms of helping non experienced practitioners in diagnosing process as well as supporting experts in their decisions, we established a methodology to ease the process and we refer to our method as FaceGP DDSS. In the methodology, digital facial image processing methods are used to reveal facial features with disorders indicating genotype-phenotype interrelation. A great number of genetic disorders indicating a characteristic pattern of facial anomalies can be typically identified by analyzing specific features with the aid of facial image processing methods such as PCA in order to determine reference values (eigenfaces) and train the system. Distance algorithms such as Euclidean, Mahalanobis are used to construct the correlation of the input image with the trained images in matching. Some image enhancement methods such as histogram equalization and median filter are implemented on detected degraded images to capture better features. This study proposes a novel computer-assisted and cost-effective method by merging several methods in the characterization of the facial dysmorphology, in particular a method relying primary on face image capture and manipulation to diagnose genetic diseases