Critical issues in Leveraging Blockchain in Healthcare Sector

Blockchain innovation has brought various benefits to the healthcare sector. Utilizing blockchains in clinical contexts will reduce handling time since when a patient signs up for a review, the complete collected data will be accessible at once because of accessibility on the distributed ledger. Also, specialists will not need to stress over the patients giving them a legit clinical history, because of their capacity to progressively see the correct, credible, and quality source-recorded information. It eliminates any likely clinical history mistakes. Similarly, the patients will not need to stress over having a second assessment from another specialist, because of the straightforwardness of the information. Having patient records on a blockchain organization will prompt individuals to know and associate with various others, across the globe, with similar ailments as they have, which is not only valuable for their well-being, but also make the patients feel acknowledged, upheld, and have reinforced determination to battle the ailment. Patients will have total independence regarding their information, and they will choose who to impart the information to. In this paper, we present all the challenges and critical issues associated with implementing blockchains in the healthcare sector

(R2028) A Brief Note on Space Time Fractional Order Thermoelastic Response in a Layer

In this study, a one-dimensional layer of a solid is used to investigate the exact analytical solution of the heat conduction equation with space-time fractional order derivatives and to analyze its associated thermoelastic response using a quasi-static approach. The assumed thermoelastic problem was subjected to certain initial and boundary conditions at the initial and final ends of the layer. The memory effects and long-range interaction were discussed with the help of the Caputo-type fractional-order derivative and finite Riesz fractional derivative. Laplace transform and Fourier transform techniques for spatial coordinates were used to investigate the solution of the temperature distribution and stress functions. Numerical investigations are also shown graphically for non-dimensional temperature and stress for different space and time fractional derivative values, respectively. In addition, some applicable limiting cases are discussed for standard equations, such as wave equation, Laplace equation, and diffusion equation

Is thrombocytosis a valid indicator of advanced stage and high mortality of gynecological cancer?

Background: Cytokines that stimulate thrombopoiesis are often elevated in cancer, and as a result, various cancers have been associated with thrombocytosis. In addition thrombocytosis has been found to be an adverse prognostic factor in many types of common cancers.Methods: A cross sectional study was designed to evaluate the factors associated with prognosis of the cases of carcinoma cervix in the Department of Gyne-Oncology, GMCH, Aurangabad from August 2016 to August 2017. Variables analysed were the sociodemographic details, literacy level, symptoms, duration, stage of the disease at diagnosis, pretreatment platelet counts were noted.Results: 85% patients were having squamous cell carcinoma, 6 % patients were having adenocarcinoma and 9% patients had adenosuamous carcinoma. 29% patients have platelet count less than 3 lakhs and 18 patients has tumour less than 4 cm.  71 % patients have platelet count more than 3 lakhs, only 6% patients belonged to early stage and 65% belonged to late stage of cancer cervix.Conclusions: Seventy one percent of the cases had platetlet count >3 lakh, of which only 6% were in early stage of disease, whereas 65% belonged to late stage of the disease. All the patients with tumour size of >4 cm had platelet count more than 3 lakh, this shows strong association of platelet count with tumour size >4 cm and advanced stage of the disease. This can be used as independent prognostic factor for prognosis of cancer cervix

A Novel System for AYUSH Healthcare Services using Classification and Regression

There are roughly 4000 AYUSH hospitals spread out across India under various councils and hospitals run by the Indian government. Today’s atmosphere makes it more challenging than ever to locate a suitable AYUSH facility for the treatment. The AYUSH Ministry provides India’s top option for healthcare delivery. The government is examining strategies to lower expenditures while enhancing patient care. We are proposing the ground-breaking idea of e-healthcare which involves various novel features like suggesting various tools to the patients those need to communicate with the healthcare professionals as per their convenience remotely. This research suggests an interactive system using Android in line with this trend. By integrating different bio-medical data sources that contain information pertinent to the hospital demographics, their inpatient procedure rates, Outpatient department, etc., we proposed a system that surveys on the various AYUSH hospitals to find. This system uses the Google Map API for tracking and highlighting the location to the nearby AYUSH hospitals with opening and closing timings. Additionally, the proposed system plays a crucial role in emergency scenarios by supporting the user in performing the necessary first aid techniques. Using this strategy, the entire system demonstrates that this research provides a superior method for making decisions than past studies

Cutaneous mastocytosis. Getting beneath the skin of the issue: a case report

An eleven month old girl presented with chronic urticaria since three months of age. There was a generalised hyperpigmented maculo-papular rash. Darier sign was positive. The skin biopsy showed plenty of spindle shaped mast cells with eosinophilic cytoplasm infiltrating the dermis and the appendiceal structures. The diagnosis of cutaneous mastocytosis (urticaria pigmentosa) was made. The child received symptomatic relief with chronic oral hydroxyzine and ranitidine therapy. Automated epinephrine self-injectors usually prescribed in this condition for self-management of anaphylactic episodes were not available. Intramuscular administration of (1:1000) diluted adrenaline via a disposable tuberculin syringe was taught to the mother. A medical bracelet containing her diagnosis and instructions in emergency was custom-made for her

Clinicopathological analysis of AUB in perimenopausal and postmenopausal women in cancer care centre: special reference to carcinoma endometrium

Background: Abnormal uterine bleeding (AUB) may be defined as any variation from normal menstrual cycle including alteration in its regularity, frequency, duration of flow and amount of blood loss. Postmenopausal bleeding is a danger sign for malignancy. The study aimed to study the histopathology spectrum of hysterectomy specimens and bleeding patterns in perimenopausal women and postmenopausal women.Methods: It was a retrospective observational study done at Government Medical College and Cancer Hospital, Aurangabad (MS) from January 2017 to January 2021. Total sample size was 100 women. Perimenopausal and postmenopausal women undergoing hysterectomy were analysed for the age, parity, etieology, histology and the malignant changes.Results: 22 cases of AUB were observed in the age group of less than 40 years. 56% cases presented with heavy menstrual bleeding 58% cases had prolonged menstrual bleeding. 36% cases had endometrial cause (harmonal disturbances), 12 % had endometrial polyp and 35 cases out of 100 had endometrial carcinoma. Both type 1 and type 2 cases of carcinoma endometrium are seen in this study.Conclusions: Excessive uterine bleeding is a common gynaecological problem in all age groups with significant patient morbidity. The spectrum of endometrial lesions seen in AUB and cancer cases shows that the histopathological examination of endometrium is gold standard diagnostic tool in evaluation of AUB and postmenopausal bleeding and there is an age specific association of endometrial lesions

Opinion mining using combinational approach for different domains

An increase in use of web produces large content of information about products. Online reviews are used to make decision by peoples. Opinion mining is vast research area in which different types of reviews are analyzed. Several issues are existing in this area. Domain adaptation is emerging issue in opinion mining. Labling of data for every domain is time consuming and costly task. Hence the need arises for model that train one domain and applied it on other domain reducing cost aswell as time. This is called domain adaptation which is addressed in this paper. Using maximum entropy and clustering technique source domains data is trained. Trained data from source domain is applied on target data to labeling purpose A result shows moderate accuracy for 5 fold cross validation and combination of source domains for Blitzer et al (2007) multi domain product dataset

A comparative evaluation of teaching and learning methodology on effective perception by Guru Shishya Parampara versus Audio-Visual Method with special reference to Trividha Roga Vishesha Vignyaniya Adhyaya

Teaching and learning methods are two important phases in educational system. In this the term education is not only the art of learning the facts but also training of the mind to think. In the present study the topic selected was Trividha Roga Vishesha Vijnyaniya Adhyaya. In this chapter the 3 folds for examination of Roga-Rogi pariksha is Aptopadesha, Pratyaksha and Anumana. Here, we had adopted the principles of Guru-Shishya Parampara and Audio-Visual method. In the present study Guru (mentor) gives his knowledge to Shishya (disciple) by adopting the principle of GSP. This study randomly enrolled 50 students of 2nd year B.A.M.S. students with an aim to compare the learning outcomes of both traditional Guru Shishya Parampara method and Audio-Visual method. Pre and post study evaluation was done by MCQ test and feedback was obtained on a questionnaire. Data obtained was analysed statically with help of Wilcoxon signed rank test and Chi square test. It is concluded that GSP was useful to enhance the learning with significance level p < 0.0001

SANIP: Shopping Assistant and Navigation for the visually impaired

The proposed shopping assistant model SANIP is going to help blind persons to detect hand held objects and also to get a video feedback of the information retrieved from the detected and recognized objects. The proposed model consists of three python models i.e. Custom Object Detection, Text Detection and Barcode detection. For object detection of the hand held object, we have created our own custom dataset that comprises daily goods such as Parle-G, Tide, and Lays. Other than that we have also collected images of Cart and Exit signs as it is essential for any person to use a cart and also notice the exit sign in case of emergency. For the other 2 models proposed the text and barcode information retrieved is converted from text to speech and relayed to the Blind person. The model was used to detect objects that were trained on and was successful in detecting and recognizing the desired output with a good accuracy and precision.Comment: 6 pages, 8 figures. arXiv admin note: text overlap with arXiv:2011.04244 by other author

Transfer and Ensemble Approach for Breast Cancer Detection and Classification Using Deep Learning

Breast cancer is a serious disease that can cause significant health problems for women worldwide. It is crucial to detect and classify breast cancer early stage so that doctors can promptly treat it and aid patients in their recovery. Many investigators have used various deep learning (DL) strategies to detect and classify breast cancer. However, due to the complexity of the problem, relying on a single DL model may not suffice to achieve high accuracy. Therefore, this study suggests a transfer and ensemble deep model for breast cancer detection and classification. The suggested model involves using pre-trained models such as Sequential, Xception, DenseNet201, VGG16, and InceptionResNetV2. The top three models are selected to collaborate and deliver the most accurate results. The proposed DL model was tested on publicly available breast BUSI datasets, demonstrating its superiority over single DL models, achieving an accuracy of 87.9% on the BUSI dataset. Additionally, the model proved to be adapTABLE to different amounts of data, making it potentially valuable in hospitals and clinics