Technology and Health Care - Volume Pre-press, issue Pre-press
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ISSN 0928-7329 (P)
ISSN
1878-7401 (E)
Impact Factor 2023: 1.6
Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured.
The following types of contributions and areas are considered:
1. Original articles:
Technology development in medicine: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine.
Significance of medical technology and informatics for healthcare: The appropriateness, efficacy and usefulness deriving from the application of engineering methods, devices and informatics in medicine and with respect to public health are discussed.
2. Technical notes:
Short communications on novel technical developments with relevance for clinical medicine.
3. Reviews and tutorials (upon invitation only):
Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented.
4. Minisymposia (upon invitation only):
Under the leadership of a Special Editor, controversial issues relating to healthcare are highlighted and discussed by various authors.
Abstract: BACKGROUND: Cervical malignancy is considered among the most perilous cancers affecting women in numerous East African and South Asian nations, both in terms of its prevalence and fatality rates. OBJECTIVE: This research aims to propose an efficient automated system for the segmentation of cancerous regions in cervical images. METHODS: The proposed techniques encompass preprocessing, feature extraction with an optimized feature set, classification, and segmentation. The original cervical image undergoes smoothing using the Gaussian Filter technique, followed by the extraction of Local Binary Pattern (LBP) and Grey Level Co-occurrence Matrix (GLCM) features from the…enhanced cervical images. LBP features capture pixel relationships within a mask window, while GLCM features quantify energy metrics across all pixels in the images. These features serve to distinguish normal cervical images from abnormal ones. The extracted features are optimized using Genetic Algorithm (GA) as an optimization method, and the optimized sets of features are classified using the Co-Active Adaptive Neuro-Fuzzy Inference System (CANFIS) classification method. Subsequently, a morphological segmentation technique is employed to categorize irregular cervical images, identifying and segmenting malignant regions within them. RESULTS: The proposed approach achieved a sensitivity of 99.09%, specificity of 99.39%, and accuracy of 99.36%. CONCLUSION: The proposed approach demonstrated superior performance compared to state-of-the-art techniques, and the results have been validated by expert radiologists.
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Abstract: BACKGROUND: Anaemia is a commonly known blood illness worldwide. Red blood cell (RBC) count or oxygen carrying capability being insufficient are two ways to describe anaemia. This disorder has an impact on the quality of life. If anaemia is detected in the initial stage, appropriate care can be taken to prevent further harm. OBJECTIVE: This study proposes a machine learning approach to identify anaemia from clinical markers, which will help further in clinical practice. METHODS: The models are designed with a dataset of 364 samples and 12 blood test attributes. The developed algorithm…is expected to provide decision support to the clinicians based on blood markers. Each model is trained and validated on several performance metrics. RESULTS: The accuracy obtained by the random forest, K nearest neighbour, support vector machine, Naive Bayes, xgboost, and catboost are 97%, 98%, 95%, 95%, 98% and 97% respectively. Four explainers such as Shapley Additive Values (SHAP), QLattice, Eli5 and local interpretable model-agnostic explanations (LIME) are explored for interpreting the model predictions. CONCLUSION: The study provides insights into the potential of machine learning algorithms for classification and may help in the development of automated and accurate diagnostic tools for anaemia.
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Abstract: BACKGROUND: The term ‘dementia’ covers a range of progressive brain diseases from which many elderly people suffer. Traditional cognitive and pathological tests are currently used to detect dementia, however, applications using Artificial Intelligence (AI) methods have recently shown improved results from improved detection accuracy and efficiency. OBJECTIVE: This research paper investigates the efficacy of one type of data analytics called supervised learning to detect Alzheimer’s disease (AD) – a common dementia condition. METHODS: The aim is to evaluate cognitive tests and common biological markers (biomarkers) such as cerebrospinal fluid (CSF) to develop predictive…classification systems for dementia detection. RESULTS: A data analytics process has been proposed, implemented, and tested against real data obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) repository. CONCLUSION: The models showed good power in predicting AD levels, notably from specified cognitive tests’ scores and tauopathy related features.
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Keywords: Alzheimer’s disease, biomarkers, data analytics, dementia, medical screening
Abstract: BACKGROUND: Endometrial receptivity is crucial for the establishment of a healthy pregnancy outcome. Previous research on endometrial receptivity primarily examined endometrial thickness, endometrial echo types, and endometrial blood supply. OBJECTIVE: To explore the differences in the elastic modulus of the endometrium in women with various pregnancy outcomes by real-time shear wave elastography (SWE) and to investigate its application value in evaluation of endometrial receptivity. METHODS: A total of 205 pregnant women who were admitted at Wenzhou People’s Hospital between January 2021 and December 2022 were selected. Three-dimensional transvaginal sonography and real-time shear wave…elastography were performed in the proliferative phase and receptive phase of the endometrium, and the average elastic modulus of the endometrium in the two phases was obtained and compared. According to whether the pregnancy was successful or not, the participants were divided into the pregnancy group (n = 72) and non-pregnancy group (n = 133), and the differences in intimal thickness, 3D blood flow parameters, and average elastic modulus of intima were compared between the two groups. RESULTS: The average elastic modulus of the endometrium in the proliferative phase and receptive phase was (23.92 ± 2.31) kPa and (11.82 ± 2.24) kPa, respectively, and the difference was statistically significant P < 0.05. The average elastic modulus of the endometrium in the pregnancy group and non-pregnancy group was (9.97 ± 1.08) kPa and (12.82 ± 2.06) kPa, respectively, and the difference was statistically significant P < 0.05. The area under the curve of predicting pregnancy by the average elastic modulus of the endometrium in the receptive phase was 0.888 (0.841∼ 0.934), with corresponding P value < 0.05. The critical value was 11.15, with a corresponding sensitivity of 81.7% and specificity of 78.2%. CONCLUSION: Real-time shear wave elastography can quantitatively evaluate endometrial elasticity, indirectly reflect the endometrial phase, and provide a new diagnostic concept for evaluating endometrial receptivity and predicting pregnancy outcome in infertile patients.
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Abstract: BACKGROUND: Commercially available oral rinses contain active ingredients with concentration that is claimed by manufacturers to be effective as antiplaque agent. To date there has been no mention of the effect of oral rinse on the adherence of early plaque colonizers in plaque formation and the concentration to be used before/after meals. OBJECTIVE: The chief aim of the study was to evaluate microbial retention on the salivary pellicle on treatment with oral rinses (CHX & EO)/PS (mimicking after meals use of mouth wash/PS). METHODS: Noordini’s Artifical Mouth model was used for developing the…single species biofilm with early microbial colonizers of oral biofilm (A. viscosus , Strep. mitis and Strep. sanguinis respectively). The microbial retention on use of oral rinses comprising of CHX and EO as an active ingredients respectively was compared with Curcumin PS. For evaluating the microbial retention, the pellicle with microbial inoculation was developed on the glass beads in the mouth model. Subsequently the respective single specie biofilm was exposed to the mouth wash and PS after inoculation. It mimicked as use of mouth wash/PS after meals. The bacterial count in the dental biofilm was evaluated on serial dilution (CFU/ml). Sterile deionized water was used as a negative control. For qualitative analysis, Scanning electron microscope (SEM) was used to evaluate the microbial count. RESULTS: From the data it was observed that for the treatment of single species experimental biofilm with commercially available mouth rinses (CHX & EO) and PS (curcumin), there was significant retention for S.mitis , S.sanguinis and A.viscosus . There was no significant difference observed between PS and CHX treated single species biofilm. Whereas a significant difference was observed between EO treated biofilms and CHX/PS treated biofilms (p ⩽ 0.05). CONCLUSION: It can be concluded from the results that curcumin PS and CHX should not be used after meals whereas EO containing mouth rinse can be used to maintain the oral mocroflora.
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Abstract: BACKGROUND: Coronary heart disease (CHD) is one of the deadliest diseases and a risk prediction model for cardiovascular conditions is needed. Due to the huge number of features that lead to heart problems, it is often difficult for an expert to evaluate these huge features into account. So, there is a need of appropriate feature selection for the given CHD dataset. For early CHD detection, deep learning modes (DL) show promising results in the existing studies. OBJECTIVE: This study aimed to develop a deep convolution neural network (CNN) model for classification with a selected number of…efficient features using the LASSO (least absolute shrinkage and selection operator) technique. Also, aims to compare the model with similar studies and analyze the performance of the proposed model using accuracy measures. METHODS: The CHD dataset of NHANES (National Health and Nutritional Examination Survey) was examined with 49 features using LASSO technique. This research work is an attempt to apply an improved CNN model for the classification of the CHD dataset with huge features CNN model with feature extractor consists of a fully connected layer with two convolution 1D layers, and classifier part consists of two fully connected layers with SoftMax function was trained on this dataset. Metrics like accuracy recall, specificity, and ROC were used for the evaluation of the proposed model. RESULTS: The feature selection was performed by applying the LASSO model. The proposed CNN model achieved 99.36% accuracy, while previous studies model achieved over 80 to 92% accuracy. CONCLUSION: The application of the proposed CNN with the LASSO model for the classification of CHD can speed up the diagnosis of CHD and appears to be effective in predicting cardiovascular disease based on risk features.
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Abstract: BACKGROUND: Computational research plays an important role in predicting the chemical and physical properties of biologically active compounds important in future structural modifications to improve or modify biological activity. OBJECTIVE: This research focuses on quantum chemical and spectroscopic investigations properties of synthesized 4-hydroxycoumarin derivatives. METHODS: Quantum chemical calculations were obtained using B3LYP, HF, and M06-2x level methods with the 6-31++G (d,p) basis set. Afterward, IR, 1 H, 13 C, UV-Visible experimentally parameters were compared with the results obtained using the B3LYP/6-31+G*(d) basis set of the…molecules to be able to characterize the structures. RESULTS: Based on the quantum chemical calculations compound with acetamido group on the phenyl ring is the most reactive, and compound with nitro substituent is the least reactive and the the strongest electrophile among tested compounds. With the exception of compounds with dimethylamino group, all other compounds have a pronounced tautomer between between OH and C = O group. The calculated and experimental values are in agreement with each other. CONCLUSION: The molecular structure in the ground state of six 3-cinnamoyl 4-hydroxycoumarin derivatives was optimized using density functional theory. The observed and computed values were compared and it can be concluded that the theoretical results were in good linear agreement with the experimental data.
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Keywords: Density functional theory (DFT), coumarin derivatives, quantum chemical calculations
Abstract: BACKGROUND: The effective treatment of breast cancer in elderly patients remains a major challenge. OBJECTIVE: To construct a nomogram affecting the overall survival of triple-negative breast cancer (TNBC) and establish a survival risk prediction model. METHODS: A total of 5317 TPBC patients with negative expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) who were diagnosed and received systematic treatment from 2010 to 2015 were collected from the American Cancer Surveillance, Epidemiology and End Results (SEER) database. They were randomly divided into training set (n =…3721) and validation set (n = 1596). Univariate and multivariate Cox regression analysis were used to identify prognostic features, and a nomogram was established to predict the probability of 1-year, 3-year and 5-year OS and BCSS. We used consistency index (C-index), calibration curve, area under the curve (AUC) and decision curve analysis (DCA) to evaluate the predictive performance and clinical utility of the nomogram. RESULTS: The C-indices of the nomograms for OS and BCSS in the training cohort were 0.797 and 0.825, respectively, whereas those in the validation cohort were 0.795 and 0.818, respectively. The receiver operating characteristic (ROC) curves had higher sensitivity at all specificity values as compared with the Tumor Node Metastasis (TNM) system. The calibration plot revealed a satisfactory relationship between survival rates and predicted outcomes in both the training and validation cohorts. DCA demonstrated that the nomogram had clinical utility when compared with the TNM staging system. CONCLUSION: This study provides information on population-based clinical characteristics and prognostic factors for patients with triple-negative breast cancer, and constructs a reliable and accurate prognostic nomogram.
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Keywords: Triple negative breast cancer, nomogram, overall survival, breast cancer-specific survival, SEER database
Abstract: BACKGROUND: The extent of the association between vitamin D deficiency and knee osteoarthritis remains inadequately understood. OBJECTIVE: This study aimed to elucidate the relationship between vitamin D levels and knee osteoarthritis through a cross-sectional analysis. METHODS: This retrospective study involved an analysis of knee radiographs and serum 25-hydroxyvitamin D3 (25-(OH) vitamin D3) levels in a cohort of 3424 individuals (2901 women and 523 men). Knee osteoarthritis severity was evaluated using the Kellgren-Lawrence radiological scoring system. RESULTS: Of the participants, 49.2% (n = 1,683) were diagnosed…with knee osteoarthritis. Among these patients, the levels of adjusted 25-(OH) vitamin D3 were significantly lower (p < 0.001). Regression analysis revealed a significant association between vitamin D deficiency and knee osteoarthritis, with an adjusted odds ratio (OR) of 1.7 (95% CI: 1.5–2.0; p < 0.001). Notably, a stronger association was observed between vitamin D deficiency and knee osteoarthritis in women under 65 compared to those aged 65 and above. CONCLUSIONS: The findings of this study indicate a higher prevalence of vitamin D deficiency in patients with knee osteoarthritis. Maintaining adequate serum 25-(OH) vitamin D3 levels may prevent knee osteoarthritis, especially in women below 65.
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