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1
Content available remote Computational intelligence techniques for medical diagnosis and prognosis: Problems and current developments
100%
Shahid A. H. , Singh M. P.
Biocybernetics and Biomedical Engineering
|
2019
|
tom Vol. 39, no. 3
638--672
EN
Diagnosis, being the first step in medical practice, is very crucial for clinical decision making. This paper investigates state-of-the-art computational intelligence (CI) techniques applied in the field of medical diagnosis and prognosis. The paper presents the performance of these techniques in diagnosing different diseases along with the detailed description of the data used. This paper includes basic as well as hybrid CI techniques that have been used in recent years so as to know the current trends in medical diagnosis domain. The paper presents the merits and demerits of different techniques in general as well as application specific context. This paper discusses some critical issues related to the medical diagnosis and prognosis such as uncertainties in the medical domain, problems in the medical data especially dealing with time-stamped (temporal) data, and knowledge acquisition. Moreover, this paper also discusses the features of good CI techniques in medical diagnosis. Overall, this review provides new insight for future research requirements in the medical diagnosis domain.
2
Content available Advanced diabetic retinopathy detection with the R-CNN: A unified visual health solution
100%
Sri Sravya V. , Naga Srinivasu P. , Shafi J. , Hołubowski W. , Zielonka A.
International Journal of Applied Mathematics and Computer Science
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2024
|
tom Vol. 34, no. 4
661--678
EN
Diabetic retinopathy (DR) can cause blindness and vision impairment. This degenerative eye condition may lead to an irreversible vision loss. The prevalence of vision impairment and blindness caused by DR emphasizes the critical need for better screening and therapy measures. DR aetiology involves persistent hyperglycemia-induced microvascular abnormalities, oxidative stress, inflammatory reactions, and retinal blood flow changes. Common screening methods for retinal issues include fundus photography, OCT, and fluorescein angiography. For those with diabetic macular edema (DME), it is a common cause of vision loss. Our goal is to develop an automated, cost-effective method for identifying diabetic retinal disease specimens. This study introduces a faster R-CNN method for detecting and classifying DR lesions in retinal images. Those are classified across five different classes. An extensive analysis of 88,704 images from a Kaggle dataset indicates the efficiency of the proposed model, with a reasonable accuracy of 98.38%. The proposed method is robust in disease localization and classification tasks and it has outperformed other existing studies in DR recognition. On evaluating cross-datasets in Kaggle and APTOS, the model has yield better results during training and testing phases.
3
Molecular beacons: a novel optical diagnostic tool
84%
Han S.-X. , Jia X. , Ma J.-L. , Zhu Q.
Archivum Immunologiae et Therapiae Experimentalis
|
2013
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tom 61
|
nr 2
4
Content available remote Review on plantar data analysis for disease diagnosis
84%
Ramirez-Bautista J. A. , Hernández-Zavala A. , Chaparro-Cárdenas S. L. , Huerta-Ruelas J. A.
Biocybernetics and Biomedical Engineering
|
2018
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tom Vol. 38, no. 2
342--361
EN
Force distribution on foot surface allows to understand the human mechanical behavior, providing detailed information for the evaluation of foot alterations. In diagnosis for diseases related to plantar pathologies, there are many devices for plantar pressure mea-surement, and corresponding algorithms for data analyzing, providing medical tools for assisting in treatment, early detection, and the development of preventive strategies. In medicine, use of computational intelligence is increasing, making the diagnostic processes faster and more accurate. Clinical Decision Support Systems (CDSS) can handle large amounts of data to improve decision-making, helping to prevent the deterioration of people's health. Numerous approaches have been applied over the past few decades to solve medical problems such as hepatitis, diabetes, liver disease, pathological gait, and plantar diseases, among others. This paper presents the developments reported in the literature for detecting diseases through plantar pressure data and the corresponding algorithms for its analysis and diagnosis, using different electronic measurements systems. Finally, we present a discussion about the future work required to improve in the field of plantar pressure diagnosis algorithms using different approaches suggested by the authors as potential candidates. In this sense, hybrid systems which include fuzzy concepts are the most promising methodology.
5
Content available Kropki kwantowe jako narzędzia diagnostyczne
84%
Gruba N. , Rejmak W. , Romanowska A. , Lesner A.
Wiadomości Chemiczne
|
2024
|
tom [Z] 78, 3-4
369--387
EN
The discovery of quantum dots (QDs) was a breakthrough event as it influenced almost every area of our lives. They are used in new technologies, the food industry, clothing production, and finally in medicine. Due to their unique properties, QDs are successfully used in the diagnosis of diseases of various origins - the so-called civilization diseases, infections and cancers. Quantum dots can also serve as tools to monitor the proteolytic activity of enzymes, effectively lowering the detection limit. Our team has been dealing with the proteolytic activity of enzymes for many years, especially in disease diagnosis, for which we also use quantum dots. In this article, we presented the main trends in the use of QDs as diagnostic tools.
6
Content available Is it possible to detect lung cancer by trained dogs?
84%
Rudnicka J. , Walczak M. , Jezierski T. , Buszewski B.
Health Problems of Civilization
|
2015
|
tom 09
|
nr 2
EN
During the illness are released volatile organic compounds with specific smell which could have in diagnosis of diseases. The first aim of the study was qualitative and quantitative analysis of exhaled breath samples obtained from patients with lung cancer, healthy volunteers and people with other lung diseases by gas chromatography-mass spectrometry. This study showed that twenty compounds propane, ethanol, isobutane, butane, propanal, 1-propanol, 2-propanol, 2-methylfuran, 2-butanone, benzene, 2-pentanone, pentanal, hexanal, cyclohexanone, 4-heptanone, 2,4-dimethylheptane, 2,3,4-trimethylhexane, 2,3,5-trimethylhexane, 4-methyloctane, α-pinene separated two research groups of patients and healthy controls. The second goal was to evaluate the sensitivity and specificity of canine scent detection using 5 station scent lineup. Among lung cancer patients and complementary samples, overall sensitivity of canine scent detection was 85.54%, while specificity was 71.84%.
7
Content available remote Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification
84%
Arji G. , Ahmadi H. , Nilashi M. , Rashid T. A. , Hassan Ahmed O. , Aljojo N. , Zainol A.
Biocybernetics and Biomedical Engineering
|
2019
|
tom Vol. 39, no. 4
937--955
EN
This paper presents a systematic review of the literature and the classification of fuzzy logic application in an infectious disease. Although the emergence of infectious diseases and their subsequent spread have a significant impact on global health and economics, a comprehensive literature evaluation of this topic has yet to be carried out. Thus, the current study encompasses the first systematic, identifiable and comprehensive academic literature evaluation and classification of the fuzzy logic methods in infectious diseases. 40 papers on this topic, which have been published from 2005 to 2019 and related to the human infectious diseases were evaluated and analyzed. The findings of this evaluation clearly show that the fuzzy logic methods are vastly used for diagnosis of diseases such as dengue fever, hepatitis and tuberculosis. The key fuzzy logic methods used for the infectious disease are the fuzzy inference system; the rule-based fuzzy logic, Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy cognitive map. Furthermore, the accuracy, sensitivity, specificity and the Receiver Operating Characteristic (ROC) curve were universally applied for a performance evaluation of the fuzzy logic techniques. This thesis will also address the various needs between the different industries, practitioners and researchers to encourage more research regarding the more overlooked areas, and it will conclude with several suggestions for the future infectious disease researches.
8
Diversity and variation in the pathogens and the diseases caused by Septoria nodorum and Septoria tritici
84%
Cooke B. M.
Hodowla Roślin, Aklimatyzacja i Nasiennictwo
|
1994
|
tom 38
|
nr 3-4
9
Content available remote Classification of plantar foot alterations by fuzzy cognitive maps against multi-layer perceptron neural network
67%
Ramirez-Bautista J. A. , Huerta-Ruelas J. A. , Kóczy L. T. , Hatwágner M. F. , Chaparro-Cárdenas S. L. , Hernández-Zavala A.
Biocybernetics and Biomedical Engineering
|
2020
|
tom Vol. 40, no. 1
404--414
EN
Load distribution analysis on foot surface allows knowing human mechanical behavior and aids the doctor in the detection of gait disorders like, the risk of foot ulcerations, leg discrepancy, and footprint alterations. Plantar pressure data combined with techniques that use integral reasoning produce easy understanding medical tools for assisting in treatment, early detection, and the development of preventive strategies. The present research compares the classification of human plantar foot alterations using Fuzzy Cognitive Maps (FCM) trained by Genetic Algorithm (GA) against a Multi-Layer Perceptron Neural Network (MLPNN). One hundred and fifty-one subject volunteers (aged 7–77) were classified previously with the flat foot (n = 70) and cavus foot (n = 81) by specialized physicians of the Piédica diagnostic center. The trial walking was conducted using plantar pressure platforms FreeMed®. The foot surface was divided into 14 areas that included toe 1 st to 5th, metatarsal joint 1st to 5th, lateral midfoot, medial midfoot, lateral heel, and medial heel. Pressure data were normalized for each area. Better performance in the classification using small amounts of data were found by using Fuzzy rather than non-Fuzzy approach.
10
Content available remote A novel deep learning-based approach for prediction of neonatal respiratory disorders from chest X-ray images
67%
Erdogan Yildirim A. , Canayaz M.
Biocybernetics and Biomedical Engineering
|
2023
|
tom Vol. 43, no. 4
635--655
EN
In recent years, many diseases can be diagnosed in a short time with the use of deep learning models in the field of medicine. Most of the studies in this area focus on adult or pediatric patients. However, deep learning studies for the diagnosis of diseases in neonatal are not sufficient. Also, since it is known that respiratory disorders such as pneumonia have a large place among the causes of neonatal death, early and accurate diagnosis of respiratory diseases in neonates is crucial. For this reason, our study aims to detect the presence of respiratory disorders through the developed deep-learning approach using chest X-ray images of patients hospitalized in the Neonatal Intensive Care Unit. Accordingly, the enhanced version of C+EffxNet, the new hybrid deep learning model, is designed to predict respiratory disorders in neonates. In this version, the features selected by PCA are combined as 100, 200, and 300, then the binary classification process was carried out. In the study, the accuracy and kappa value were obtained as 0.965, and 0.904, respectively before feature merging, while these values were obtained as 0.977, and 0.935 after feature merging. This method, which was developed for the diagnosis of respiratory disorders in neonates, was also subsequently applied to a chest X-ray dataset that is frequently used in the literature for the diagnosis of pediatric pneumonia. For this data set, while the accuracy was 0.992, the kappa value was 0.982. The results obtained confirm the success of the proposed method for both datasets.
11
Content available Test ELISA jego modyfikacje
67%
Zacharzewska B. , Treder K.
Ziemniak Polski
|
2014
|
tom 24
|
nr 1
12
Badanie kotów w schroniskach pod kątem dermatofitozy nie musi trwać wieczność
59%
Nappier M.
Weterynaria po Dyplomie
|
2019
|
tom 20
|
nr 3
13
Sondy fluorescencyjne jako czujniki biomolekuł
59%
Szwaczko K.
Laboratorium - Przegląd Ogólnopolski
|
2024
|
tom nr 1
47--51
PL
Sondy luminescencyjne znajdują zastosowanie w różnych dziedzinach medycyny, takich jak: obrazowanie molekularne, badania nad chorobami, diagnostyka i monitorowanie procesów biologicznych. Dzięki swojej zdolności do precyzyjnego oznaczania i obrazowania różnych składników lub procesów w organizmach stanowią cenne narzędzie w badaniach laboratoryjnych i klinicznych. W niniejszym artykule zostanie przedstawiony potencjał obrazowania luminescencyjnego w diagnostyce schorzeń związanych z niewłaściwym poziomem związków tiolowych w komórkach.
EN
Luminescent probes are used in various medical fields, such as molecular imaging, research on diseases, diagnostics, and monitoring of biological processes. With their ability to accurately determine and image various components or processes in organisms, they are a valuable tool in laboratory testing and clinical research. This article presents the potential of luminescence imaging in the diagnosis of diseases associated with inappropriate levels of thiol compounds in cells.
14
Choroby pomidorow. Jak rozpoznawac? Czym zwalczac?
51%
Leski B.
Agrochemia
|
1999
|
nr 06
37-38
15
Rozwoj rdzy brunatnej oraz cechy diagnostyczne rdzy brunatnej [Puccinia recondita Rob. ex Desm] i rdzy zdzblowej [Puccinia graminis Pers.] pszenicy
51%
Zamorski C.
Biuletyn Instytutu Hodowli i Aklimatyzacji Roślin
|
1995
|
tom 194
189-192
16
Choroba zwyrodnieniowa stawów u kotów - rozpoznaj i zmniejsz cierpienie pacjenta
51%
Gaumnitz J.
Weterynaria po Dyplomie
|
2019
|
tom 20
|
nr 3
17
Podejrzenie krwawienia do światła przewodu pokarmowego? Co zrobić, kiedy nie widać krwi
51%
Collins A.
Weterynaria po Dyplomie
|
2019
|
tom 20
|
nr 3
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