Technology and Health Care - Volume 32, issue 4

Authors: Kasiviswanathan, Sivachandar | Vijayan, Thulasi Bai

Article Type: Research Article

Abstract: BACKGROUND: Artificial Intelligence (AI) plays a pivotal role in the diagnosis of health conditions ranging from general well-being to critical health issues. In the realm of health diagnostics, an often overlooked but critical aspect is the consideration of cost-sensitive learning, a facet that this study prioritizes over the non-invasive nature of the diagnostic process whereas the other standard metrics such as accuracy and sensitivity reflect weakness in error profile. OBJECTIVE: This research aims to investigate the total cost of misclassification (Total Cost) by decision rule Machine Learning (ML) algorithms implemented in Java platforms such as DecisionTable, …JRip, OneR, and PART. An augmented dataset with conjunctiva images along candidates’ demographic and anthropometric features under supervised learning is considered with a specific emphasis on cost-sensitive classification. METHODS: The opted decision rule classifiers use the text features, additionally the image feature ‘a* value of CIELAB color space’ extracted from the conjunctiva digital images as input attributes. The pre-processing consists of amalgamating text and image features on a uniform scale, normalizing. Then the 10-fold cross-validation enables the classification of samples into two categories: the presence or absence of the anemia. This study utilizes the Cost Ratio (ρ ) extracted from the cost matrix to meticulously monitor the Total Cost in four different cost ratio methodologies namely Uniform (U), Uniform Inverted (UI), Non-Uniform (NU), and Non-Uniform Inverted (NUI). RESULTS: It has been established that the PART classifier stands out as the top performer in this binary classification task, yielding the lowest mean total cost of 629.9 compared to other selected classifiers. Moreover, it demonstrates a comparatively lower standard deviation 335.9, and lower total cost across all four different cost ratio methodologies. The ranking of algorithm performance goes as follows: PART, JRIP, DecisionTable, and OneR. CONCLUSION: The significance of adopting a cost-sensitive learning approach is emphasized showing the PART classifier’s consistent performance within the proposed framework for learning the anemia dataset. This emphasis on cost-sensitive learning not only enhances the recommendations in diagnosis but also holds the potential for substantial cost savings and makes it a noteworthy focal point in the advancement of AI-driven health care. Show more

Keywords: Cost matrix, cost ratio, cost sensitive classifier, decision rule classifier, DecisionTable, JRip, OneR, PART

DOI: 10.3233/THC-231946

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2733-2753, 2024

Authors: Alhamoudi, Fahad Hussain

Article Type: Research Article

Abstract: BACKGROUND: The accuracy of dental crowns is crucial for their longevity and effectiveness. OBJECTIVE: This study aims to investigate how the precision of crowns is affected by two different fabrication methods, either subtractive (milling) or additive (3D printing), within computer-aided design/computer-aided manufacture (CAD/CAM) technology. METHODS: A standardised digital scan of a maxillary first molar with a shoulder margin (.stl file) was used to design and fabricate crowns through both subtractive (milling) and additive (3D printing) processes. The crowns’ marginal and internal fits were assessed comprehensively. Statistical analysis, including two-way ANOVA and independent t-tests, …revealed significant differences in fitting accuracy between the two methods. RESULTS: Crowns produced via 3D printing demonstrated superior fitting with minimal marginal (14 ± 5 μ m) and internal discrepancies (22 ± 5 μ m) compared to milling (marginal: 22 ± 4 μ m, internal: 23 ± 3 μ m), indicating a statistically significant advantage in precision (p ⁢ s ⩽ 0.022 for marginal fit). CONCLUSION: The findings suggest that 3D printing may offer a more accurate alternative to milling in the fabrication of digital dental prostheses, potentially revolutionising the field with its enhanced precision capabilities. Show more

Keywords: Digital crowns, CAD/CAM, milling, 3D Printing, fit accuracy, dental material, 3D scanner

DOI: 10.3233/THC-231961

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2755-2768, 2024

Authors: Zuo, Wanzhao | Li, Jing | Zuo, Mingyan | Li, Miao | Zhou, Shuang | Cai, Xing

Article Type: Research Article

Abstract: BACKGROUND: It is difficult to differentiate between chronic obstructive pulmonary disease (COPD)-peripheral bronchogenic carcinoma (COPD-PBC) and inflammatory masses. OBJECTIVE: This study aims to predict COPD-PBC based on clinical data and preoperative Habitat-based enhanced CT radiomics (HECT radiomics) modeling. METHODS: A retrospective analysis was conducted on clinical imaging data of 232 cases of postoperative pathological confirmed PBC or inflammatory masses. The PBC group consisted of 82 cases, while the non-PBC group consisted of 150 cases. A training set and a testing set were established using a 7:3 ratio and a time cutoff point. In …the training set, multiple models were established using clinical data and radiomics texture changes within different enhanced areas of the CT mass (HECT radiomics). The AUC values of each model were compared using Delong’s test, and the clinical net benefit of the models was tested using decision curve analysis (DCA). The models were then externally validated in the testing set, and a nomogram of predicting COPD-PBC was created. RESULTS: Univariate analysis confirmed that female gender, tumor morphology, CEA, Cyfra21-1, CT enhancement pattern, and Habitat-Radscore B/C were predictive factors for COPD-PBC (P < 0.05). The combination model based on these factors had significantly higher predictive performance [AUC: 0.894, 95% CI (0.836–0.936)] than the clinical data model [AUC: 0.758, 95% CI (0.685–0.822)] and radiomics model [AUC: 0.828, 95% CI (0.761–0.882)]. DCA also confirmed the higher clinical net benefit of the combination model, which was validated in the testing set. The nomogram developed based on the combination model helped predict COPD-PBC. CONCLUSION: The combination model based on clinical data and Habitat-based enhanced CT radiomics can help differentiate COPD-PBC, providing a new non-invasive and efficient method for its diagnosis, treatment, and clinical decision-making. Show more

Keywords: Nomograms, retrospective studies, antigen CYFRA21.1, area under curve, radiomics, tomography, X-ray computed, clinical decision-making, pulmonary disease, chronic obstructive

DOI: 10.3233/THC-231980

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2769-2781, 2024

Authors: Maheshwaran, Bipin | Chokkatt, Jerry Joe | Shenoy, Amrutha | Ganapathy, Dhanraj | Yadalam, Pradeep Kumar | Marrapodi, Maria Maddalena | Cicciù, Marco | Minervini, Giuseppe

Article Type: Research Article

Abstract: BACKGROUND: Titanium nanoparticles (NPs) offer promising applications in the treatment and prevention of inflammatory disorders due to their unique physicochemical characteristics. However, additional research is necessary to attain a thorough comprehension and validate the efficacy of this approach in dental practice. OBJECTIVE: This study scrutinizes the anti-inflammatory properties of a dental varnish infused with ginger and rosemary extracts mediated by titanium dioxide (TiO2) nanoparticles. METHODS: A herbal dental varnish was formulated by integrating ginger and rosemary extracts with titanium dioxide nanoparticles at concentrations of 10, 20, 30, 40, and 50 μ L. …Anti-inflammatory properties were assessed through Bovine Serum Albumin denaturation and membrane stabilization assays, comparing results with a control group. RESULTS: The results reveal concentration-dependent antioxidant and anti-inflammatory properties in the test group when compared to the control group. The BSA assay corroborates increased percent inhibition with rising titanium dioxide nanoparticle concentrations. In line with existing literature, titanium dioxide nanoparticles enhance dental material properties. CONCLUSION: The bioactive compounds in ginger and rosemary, such as phenolic compounds and terpenes, contribute to anti-inflammatory and antioxidant effects of the varnish. Additionally, the therapeutic potential of titanium dioxide nanoparticles in addressing inflammatory diseases underscores their significance in this formulation. Show more

Keywords: Preventive dentistry, nanoparticles, titanium dioxide, green synthesis, antioxidant

DOI: 10.3233/THC-231994

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2783-2792, 2024

Authors: Hu, Qinghua | Li, Min | Jiang, Linwen | Liu, Mei

Article Type: Research Article

Abstract: BACKGROUND: Photoplethysmography (PPG) signals are sensitive to motion-induced interference, leading to the emergence of motion artifacts (MA) and baseline drift, which significantly affect the accuracy of PPG measurements. OBJECTIVE: The objective of our study is to effectively eliminate baseline drift and high-frequency noise from PPG signals, ensuring that the signal’s critical frequency components remain within the range of 1 ∼ 10 Hz. METHODS: This paper introduces a novel hybrid denoising method for PPG signals, integrating Variational Mode Decomposition (VMD) with an improved wavelet threshold function. The method initially employs VMD to …decompose PPG signals into a set of narrowband intrinsic mode function (IMF) components, effectively removing low-frequency baseline drift. Subsequently, an improved wavelet thresholding algorithm is applied to eliminate high-frequency noise, resulting in denoised PPG signals. The effectiveness of the denoising method was rigorously assessed through a comprehensive validation process. It was tested on real-world PPG measurements, PPG signals generated by the Fluke ProSim™ 8 Vital Signs Simulator with synthesized noise, and extended to the MIMIC-III waveform database. RESULTS: The application of the improved threshold function let to a substantial 11.47% increase in signal-to-noise ratio (SNR) and an impressive 26.75% reduction in root mean square error (RMSE) compared to the soft threshold function. Furthermore, the hybrid denoising method improved SNR by 15.54% and reduced RMSE by 37.43% compared to the improved threshold function. CONCLUSION: This study proposes an effective PPG denoising algorithm based on VMD and an improved wavelet threshold function, capable of simultaneously eliminating low-frequency baseline drift and high-frequency noise in PPG signals while faithfully preserving their morphological characteristics. This advancement establishes the foundation for time-domain feature extraction and model development in the domain of PPG signal analysis. Show more

Keywords: Variational mode decomposition, denoising, improved wavelet thresholding, photoplethysmography

DOI: 10.3233/THC-231996

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2793-2814, 2024

Authors: Hao, Xianjie | Yi, Yanli | Lin, Xian | Li, Jie | Chen, Cheng | Shen, Yanfeng | Sun, Yuhang | He, Jinglan

Article Type: Research Article

Abstract: BACKGROUND: Psychological factors are a risk factor for the incidence of breast cancer and have a significant impact on patient prognosis. OBJECTIVE: The present study aims to investigate the effects of personalised graded psychological intervention on negative emotion and quality of life in patients with breast cancer. METHODS: A total of 200 patients with breast cancer were randomly divided into two groups: an experimental group (n = 100) and control group (n = 100). Both groups received routine nursing care. The experimental group …received personalised graded psychological intervention care, and the control group received routine nursing measures. After 2 months of standard treatment, the patients’ quality of life and negative emotions were evaluated using the self-rating depression scale (SDS), self-rating anxiety scale (SAS), social support rating scale (SSRS) and quality of life measurement scale (FACT-B) scoring criteria. RESULTS: There were no significant differences in the general data between the two groups (p > 0.05). Furthermore, there were no significant differences in the SDS, SAS, SSRS and FACT-B scores between the two groups before personalised graded psychological intervention (p > 0.05). After the intervention, the experimental group exhibited an improved nursing effect compared with the control group. The SDS and SAS scores were lower in the experimental group than in the control group (p < 0.05); after the intervention, the SDS and SAS scores were significantly lower in the experimental group than in the control group (p < 0.05). The SSRS and FACT-B scores were higher in the experimental group than in the control group (p < 0.05), and the experimental group’s post-intervention SSRS and FACT-B scores were significantly higher than before the intervention (p < 0.05). CONCLUSIONS: The use of personalised graded psychological intervention for the nursing of patients with breast cancer in clinical practice can significantly reduce patients’ negative emotions as well as improve positive emotions and quality of life; thus, this method can be popularised in the nursing process. Show more

Keywords: Personalised grading, breast cancer, psychological intervention, negative emotions, quality of life

DOI: 10.3233/THC-232021

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2815-2823, 2024

Authors: Batool, Syeda Aqsa | Chaudhry, Sana | Munir, Nadia | Inayat, Naveed | Suleman, Ghazala | Ahmed, Abdul Razzaq | Al-Qarni, Mohammed A. | Chaturvedi, Mudita | Cicciù, Marco | Minervini, Giuseppe

Article Type: Research Article

Abstract: BACKGROUND: The radiation released at the time of dental panoramic radiographs causes genotoxic and cytotoxic effects on epithelial cells. OBJECTIVE: This research aimed to evaluate the changes in the frequencies of micronucleated cells in patients’ buccal epithelial cells following dental panoramic radiography. METHODS: 74 patients were recruited for the study who were advised for panoramic radiographs. Using a wooden spatula, the buccal epithelial cells were scraped from both cheeks before to panoramic radiation exposure and ten days after the panoramic radiation exposure. Giemsa stain was used to stain the cells, and 500 cells …were scored on a slide to determine the frequency of micronuclei. To determine the difference between the frequency of micronuclei before and after radiation exposure, a paired t -test was used in the statistical analysis. RESULTS: The proportion of micronuclei cells was 0.11% before radiation exposure and 0.57% following radiation exposure after 10 days. A statistically significant increase in the frequencies of micronuclei was noted after radiation exposure values. CONCLUSION: This study revealed the genotoxicity of epithelial cells with dental panoramic radiation exposure. It is advised to reduce the use of such radiographs and to use only when there is no other diagnostic tool that is helpful or when absolutely essential. Show more

Keywords: Panoramic radiography, cytotoxic, micronuclei

DOI: 10.3233/THC-240072

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2825-2836, 2024

Authors: Celebioglu, Cansu | Topalli, Ayca Kumluca

Article Type: Research Article

Abstract: BACKGROUND: Incubators, especially the ones for babies, require continuous monitoring for anomaly detection and taking action when necessary. OBJECTIVE: This study aims to introduce a system in which important information such as temperature, humidity and gas values being tracked from incubator environment continuously in real-time. METHOD: Multiple sensors, a microcontroller, a transmission module, a cloud server, a mobile application, and a Web application were integrated Data were made accessible to the duty personnel both remotely via Wi-Fi and in the range of the sensors via Bluetooth Low Energy technologies. In addition, potential emergencies …were detected and alarm notifications were created utilising a machine learning algorithm. The mobile application receiving the data from the sensors via Bluetooth was designed such a way that it stores the data internally in case of Internet disruption, and transfers the data when the connection is restored. RESULTS: The obtained results reveal that a neural network structure with sensor measurements from the last hour gives the best prediction for the next hour measurement. CONCLUSION: The affordable hardware and software used in this system make it beneficial, especially in the health sector, in which the close monitoring of baby incubators is vitally important. Show more

Keywords: Biomedical, cloud service, healthcare, incubators, machine learning, mobile applications, web application, child wellbeing

DOI: 10.3233/THC-240167

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2837-2846, 2024

Authors: Luschi, Alessio

Article Type: Letter

DOI: 10.3233/THC-231784

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2847-2849, 2024

Article Type: Retraction

DOI: 10.3233/THC-231589

Citation: Technology and Health Care, vol. 32, no. 4, pp. 2851-2851, 2024