Technology and Health Care - Volume 32, issue 6

Authors: Hao, Huawen | Qiao, Wei | Wu, Yaguang

Article Type: Research Article

Abstract: BACKGROUND: The rapid growth of cities has been accompanied by problems with urban air quality, making air pollution challenging to manage. In this situation, people focus on indoor building materials to improve air quality. OBJECTIVE: In this paper, a novel bola-type surfactant was synthesized and used as a template, using ethyl orthosilicate and sodium meta-aluminate as the silicon and aluminum source, in the ratio of n (NaOH ): n (NaAIO2 ): n (SiO2 ): n (SDA ): n (H2 O) as 30:2.5:120:5:4800. …METHODS: Hydrothermal preparation of ZSM-5 molecular sieves with a nanosheet structure (H-ZSM-5) was accomplished. The manufactured lamellar ZSM-5 molecular sieves were examined using X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and adsorption and desorption techniques. RESULTS: Traditional microporous ZSM-5 had a considerably lower static adsorption of formaldehyde molecules. The findings demonstrated that the nano-lamellar H-ZSM-5 molecular sieve can purify and eliminate larger molecular VOCs inside because it has the ability to adsorb larger molecular diameter VOCs. Additionally, the effectiveness of the adsorption was assessed using toluene vapour molecules with higher molecular diameters. CONCLUSION: The findings demonstrate that the nanosheet H-ZSM-5 molecular sieve can remove bigger molecule VOCs from indoor air and can be utilised to purify indoor spaces. This study offers a fresh approach to indoor environmental cleanup by demonstrating the capability of nano-lamellar H-ZSM-5 molecular sieves for molecular adsorption. Show more

Keywords: Bola-type surfactant, H-ZSM-5, formaldehyde, toluene, adsorption

DOI: 10.3233/THC-240187

Citation: Technology and Health Care, vol. 32, no. 6, pp. 5009-5023, 2024

Authors: Pandey, Anand | Singh, Ajeet | Boyapati, Prasanthi | Chaturvedi, Abhay | Purushotham, N. | M, Sangeetha

Article Type: Research Article

Abstract: BACKGROUND: Heart disease represents the leading cause of death globally. Timely diagnosis and treatment can prevent cardiovascular issues. An Electrocardiograms (ECG) serves as a diagnostic tool for identifying heart difficulties. Cardiovascular Disease (CVD) often gets identified through ECGs. Deep learning (DL) garners attention in healthcare due to its potential in swiftly diagnosing ECG anomalies, crucial for patient monitoring. Conversely, automatic CVD detection from ECGs poses a challenging task, wherein rule-based diagnostic models usually achieve top-notch performance. These models encounter complications in supervision vast volumes of diverse data, demanding widespread analysis and medical capability to ensure precise CVD diagnosis. …OBJECTIVE: This study aims to enhance cardiovascular disease diagnosis by combining symptom-based detection and ECG analysis. METHODS: To enhance these experiments, we built a novel automated prediction method based on a Feed Forward Neural Network (FFNN) model. The fundamental objective of our method is to develop the accuracy of ECG diagnosis. Our strategy employs chaos theory and destruction analysis to combine optimum deep learning features with a well-organized set of ECG properties. In addition, we use the constant-Q non-stationary Gabor transform (CQNGT) to convert one-dimensional ECG data into a two-dimensional picture. A pre-trained FFNN processes this image. To identify significant features from the FFNN output that correspond with the ECG data, we employ pairwise feature proximity. RESULTS: According to experimental findings, the suggested system, FFNN-CQNGT, surpasses other state-of-the-art systems in terms of precision of 94.89%, computational efficiency of 2.114 ms, accuracy of 95.55%, specificity of 93.77%, and sensitivity of 93.99% and MSE 40.32%. CONCLUSION: Contributing an automated ECG-based DL system based on FFNN-CQNGT for early-stage cardiovascular disease identification and classification holds great potential for both patient care and public health. Show more

Keywords: Cardiovascular Disease (CVD), Electrocardiograms (EEG), Feed Forward Neural Network (FFNN), constant-Q non-stationary Gabor transform (CQNGT)

DOI: 10.3233/THC-240543

Citation: Technology and Health Care, vol. 32, no. 6, pp. 5025-5045, 2024

Authors: Li, Xia | Dong, Lili

Article Type: Research Article

Abstract: BACKGROUND: Breast cancer (BC) is one of the most common malignancies in women and imposes a significant health burden globally. According to data from the World Health Organization, the incidence of BC has been increasing steadily over the years. It has become one of the leading causes of cancer-related death among women worldwide. OBJECTIVE: This work was to evaluate the combined intervention effect of psychological care along with the use of ondansetron, dexamethasone, and promethazine hydrochloride in breast cancer (BC) patients undergoing chemotherapy, including their impact on nausea and vomiting control, quality of life (QoL), and …psychological status. METHODS: 64 BC patients undergoing chemotherapy were collected and randomly rolled into a control group (Group C) and an intervention group (Group I). Group C received ondansetron combined with routine psychological support and counseling therapy, while Group I received a combination of ondansetron, dexamethasone, promethazine hydrochloride, and psychological care therapy. Self-assessment scores for anxiety, QoL ratings, white blood cell counts, and incidence of adverse reactions were assessed and compared between the two groups. RESULTS: Group I showed better control of nausea and vomiting versus Group C (P < 0.05). Marked improvements were also observed in the self-rating anxiety scale (SAS) scores, white blood cell counts, and nursing satisfaction in Group I versus Group C (P < 0.05). Nevertheless, the two groups had no significant difference regarding QoL scores (P > 0.05). CONCLUSION: the combination of psychological care with ondansetron, dexamethasone, and promethazine hydrochloride effectively controls nausea and vomiting symptoms in BC patients undergoing chemotherapy and provides higher levels of clinical nursing satisfaction. Show more

Keywords: Chemotherapy for breast cancer, psychological nursing, ondansetron, dexamethasone, promethazine hydrochloride

DOI: 10.3233/THC-240695

Citation: Technology and Health Care, vol. 32, no. 6, pp. 5047-5063, 2024

Authors: Yang, Xi | Zhang, Jianmei | Liang, Yanyan

Article Type: Research Article

Abstract: BACKGROUND: Myopia is a frequent visual problem, and the relationship between choroidal thickness (CT) and the degree of myopia has been a hot topic in myopia research. OBJECTIVE: This work aimed to explore the correlation between CT and the degree of myopia, providing a reference for diagnosing and treating myopia. METHODS: A cross-sectional study was conducted from September 2021 to December 2022, collecting data from 95 myopic patients aged between 18 and 50 years in the outpatient department. All subjects’ CT in the macular center (MC), spherical equivalent (SE), and other ocular parameters …were measured. Furthermore, the Pearson correlation coefficient (PCC) analyzed relationships between CT and various factors. RESULTS: The choroid was thickest in the MC and gradually became thinner towards the periphery, with the thinnest region located nasally in the healthy group. In the mild, moderate, and severe myopia groups, the choroid was thickest at 1,000 μ m temporal to the fovea, becoming thinner towards the periphery, with the thinnest region located nasally. The MC’s CT was correlated with a family history of myopia, SE, axial length (AL), and intraocular pressure (IOP). Meanwhile, there was a negative linear relationship between AL and CT in the MC (standard coefficient (SC) of - 0.596, P -value of 0.000, tolerance of 0.217, and variance inflation factor (VIF) of 4.467), and a positive linear correlation between SE and CT in the MC (SC of 0.205, P -value of 0.013, tolerance of 0.257, and VIF of 3.792). CONCLUSION: This work provided clues for further understanding of the pathogenesis of myopic eyes and served as a scientific basis for early screening and treatment of myopia. Additionally, investigating the correlation between myopia and CT can also yield a reference for developing personalized myopia management strategies, which will help slow down myopia’s progression and prevent related complications. Show more

Keywords: Choroidal thickness in the macular center, myopia, spherical equivalent, axial length, linear correlation

DOI: 10.3233/THC-240761

Citation: Technology and Health Care, vol. 32, no. 6, pp. 5065-5080, 2024

Authors: Anjikumar, Tamarapalli | Chakravarthy, A.S.N.

Article Type: Research Article

Abstract: BACKGROUND: In the Healthcare (HC) sector, the usage of Wireless Sensor Healthcare Networks (WSHN) is attaining specific importance. The sensor device is implanted into the patient’s body, and the sensed health information of patients is transformed via data aggregating devices like mobile devices, cameras, and so on, to the doctors. Thus, the early signs of diseases are identified, and remote monitoring of the patient’s health is carried out by the physician on time. This aids in improving the health condition of the people and reduces the severity of disorders. But, the security gap in HC remains unresolved, despite various …advantages. OBJECTIVE: This work proposes secured data communication in WSHN using Exponential Message Digest5 (EXP-MD5) and Diffie Hellman Secret Key-based Elliptic Curve Cryptography (DHSK-ECC) techniques. METHODS: Primarily, the patient registers their details in the Hospital Cloud Server (HCS). With hospital ID and patient ID, public and private keys are generated during registration. Afterward, by utilizing the Navie Shuffling (NS) technique, n Cr combinations are created and shuffled. After shuffling, any of the randomly selected combinations are encoded utilizing the American Standard Code for Information Interchange (ASCII) code. For patient authentication, the ASCII code is further converted into a Quick Response(QR) code. Upon successful registration, the patient logs in to HCS. The patient can book for doctor’s appointment if the login details are verified with those of the registered details. On consulting the doctor at the pre-informed time, the digital signature is created utilizing the Universal Unique Salt-based Digital Signature Algorithm (UUS-DSA) for authenticating the patient details. Further, for providing accessibility to all the authorized patients, the registered patients on HCS are considered as nodes. Then, an authorized path is created using the EXP-MD5 technique to protect each individual patient’s details. The patient’s IoT data is sensed, followed by authorized path creation. The data is encrypted via the DHSK-ECC algorithm for secure data transmission. Lastly, all the information is stored in HCS, so that the patient’s health condition is regularly monitored by the doctor and the needy advice is suggested to the patients in the future. Also, hash matching is carried out when the doctor needs to access data. RESULTS: The proposed technique’s efficacy is validated by the performance analysis in comparison with other conventional techniques. CONCLUSION: In this proposed research, the authentication is performed in multiple scenarios to enhance data security and user privacy. The patient details are authenticated during registration and verification to access the online consultation only by the authorized person. Further, the patient health information is encrypted in the proposed work after consultation so that the intrusion of medical records by malicious users and data tampering is prevented. Also, the sensed data gathered from patients are transferred to the HCS by creating the authorized path, which further enhances the security of patient data. Thus, the data communication of the WSHN is well-secured in this work through multi-level authentication and improved cryptography techniques. Show more

Keywords: Data security, privacy-preserving, healthcare networks, Universal Unique Salt-based Digital Signature Algorithm (UUS-DSA), Hospital Cloud Server (HCS), Diffie Hellman Secret Key-based Elliptic Curve Cryptography (DHSK-ECC)

DOI: 10.3233/THC-240790

Citation: Technology and Health Care, vol. 32, no. 6, pp. 5081-5103, 2024

Authors: Gayathri D, Bala | Sangeetha, D.

Article Type: Research Article

Abstract: BACKGROUND: In the modern medical industry, sensors and other medical electronic equipment such as ECG, thermometers, etc. that measure vitals like blood pressure, body temperature, heartbeat, and blood cells are used to record patient data. The information gathered helps to create a patient profile, which in turn helps doctors treat patients appropriately and helps users gain insights into their health. But, the information collected is regionally specific and not worldwide. Thus, this may create problems in transparency, integrity, and much more. The medical details of patients collected are stored in a simple database which appears to be a centralized …application that is prone to be modified or hacked by intruders and also suffers from fault tolerance. OBJECTIVE: This paper aims to solve this problem using Blockchain and Data Possession methodologies. METHODS: Blockchain helps to store multiple copies of data in a decentralized fashion. Thus, a secured model could be implemented using blockchain in which the patient’s data can be securely sent to any medical professional, thus promoting transparency, security, and integrity. RESULTS: Provable Data Possession helps the users to verify that their information is intact and has not been tampered. It can be achieved using cryptography which encrypts the information of the patients stored. CONCLUSION: This paper will be beneficial for the medical department and the public such that it will be beneficial in terms of transparency, scalability, and security. Show more

Keywords: Blockchain, provable data possession, SQL injection attacks, machine learning, neural networks, cryptography

DOI: 10.3233/THC-240921

Citation: Technology and Health Care, vol. 32, no. 6, pp. 5105-5127, 2024

Authors: Liu, Dongquan | Zhao, Yonggang | Liu, Bangquan

Article Type: Research Article

Abstract: BACKGROUND: Pulmonary nodule, one of the most common clinical phenomena, is an irregular circular lesion with a diameter of ⩽ 3 cm in the lungs, which can be classified as benign or malignant. Differentiating benign and malignant pulmonary nodules has an essential effect on clinical medical diagnosis. OBJECTIVE: To explore the clinical value and diagnostic effects of the lung nodule classification and segmentation algorithm based on deep learning in differentiating benign and malignant pulmonary nodules. METHODS: A deep learning model with a fine-grained classification manner for the discrimination of pulmonary …models in Dr.Wise Lung Analyzer. This study retrospectively enrolled 120 patients with pulmonary nodules detected by chest spiral CT from March 2021 to September 2022 in the radiology department of Ninghai First Hospital. The DL-based method and physicians’ accuracy, sensitivity, and specificity results were compared using the pathological results as the gold standard. The ROC curve of the deep learning model was plotted, and the AUCs were calculated. RESULTS: On 120 CT images, pathologically diagnosed 81 malignant nodules and 122 benign modules. The AUCs of radiologists’ diagnostic approach and DL-base method for differentiating patients were 0.62 and 0.81; radiologists’ diagnostic approach and DL-base method achieved AUCs of 0.75 and 0.90 for benign and malignant pulmonary nodules differentiate. The accuracy, sensitivity, and specificity with the deep learning model were 73.33%, 78.75%, and 62.50%, respectively, while the accuracy, sensitivity, and specificity with the physician’s diagnosis were 63.33%, 66.25%, and 57.500. CONCLUSION: There was no significant difference between the diagnosis results of the proposed DL-based method and the radiologists’ diagnostic approach in differentiating benign and malignant lung nodules on spiral CT (P < 0.05). Show more

Keywords: Benign and malignant pulmonary nodule, deep learning, diagnosis, early diagnosis

DOI: 10.3233/THC-241079

Citation: Technology and Health Care, vol. 32, no. 6, pp. 5129-5140, 2024

Authors: Kong, Yang | Wang, Yizhi | Yang, Qifan | Ye, Song

Article Type: Research Article

Abstract: BACKGROUND: Bibliometric analysis of liver cancer research, particularly in immunotherapy, reveals crucial insights. The US leads in liver cancer mortality but ranks fifth globally. OBJECTIVE: Scopus database analysis identified 2,349 papers, with the top 100 ranging from 127 to 4,959 citations. Notably, “Microenvironmental Regulation of Tumours Progression and Metastasis” in the Journal of Nature Medicine garnered the highest citations. METHODS: Journals like the Journal of Hepatology, Hepatology, and Nature Reports Clinical Oncology contributed significantly. Understanding molecular mechanisms and prognostic indicators is paramount for advancing combination therapies. RESULTS: For better patient …outcomes, research trends in liver cancer immunotherapy point to improved treatment protocols, knowledge of the tumor microenvironment, combining therapies, predicting disease course, international cooperation, sophisticated surgical techniques, early detection, oncolytic virotherapy, and patient-centered care. CONCLUSIONS: This research underscores immunotherapy’s pivotal role and encourages further exploration, offering valuable insights into liver cancer treatment trends. Show more

Keywords: Liver cancer, immunotherapy, bibliometric analysis, research trends, oncology

DOI: 10.3233/THC-241111

Citation: Technology and Health Care, vol. 32, no. 6, pp. 5141-5155, 2024