Performance analysis and comparison of Machine Learning and LoRa-based Healthcare model.

Diabetes Mellitus (DM) is a widespread condition that is one of the main causes of health disasters around the world, and health monitoring is one of the sustainable development topics. Currently, the Internet of Things (IoT) and Machine Learning (ML) technologies work together to provide a reliable method of monitoring and predicting Diabetes Mellitus. In this paper, we present the performance of a model for patient real-time data collection that employs the Hybrid Enhanced Adaptive Data Rate (HEADR) algorithm for the Long-Range (LoRa) protocol of the IoT. On the Contiki Cooja simulator, the LoRa protocol's performance is measured in terms of high dissemination and dynamic data transmission range allocation. Furthermore, by employing classification methods for the detection of diabetes severity levels on acquired data via the LoRa (HEADR) protocol, Machine Learning prediction takes place. For prediction, a variety of Machine Learning classifiers are employed, and the final results are compared with the already existing models where the Random Forest and Decision Tree classifiers outperform the others in terms of precision, recall, F-measure, and receiver operating curve (ROC) in the Python programming language. We also discovered that using k-fold cross-validation on k-neighbors, Logistic regression (LR), and Gaussian Nave Bayes (GNB) classifiers boosted the accuracy.

A Survey of Soft Computing Approaches in Biomedical Imaging.

Medical imaging is an essential technique for the diagnosis and treatment of diseases in modern clinics. Soft computing plays a major role in the recent advances in medical imaging. It handles uncertainties and improves the qualities of an image. Until now, various soft computing approaches have been proposed for medical applications. This paper discusses various medical imaging modalities and presents a short review of soft computing approaches such as fuzzy logic, artificial neural network, genetic algorithm, machine learning, and deep learning. We also studied and compared each approach used for other imaging modalities based on the certain parameter used for the system evaluation. Finally, based on comparative analysis, the possible research strategies for further development are proposed. As far as we know, no previous work examined this issue.

CT Image Reconstruction Using NLMfuzzyCD Regularization Method.

Aims and Scope: Computed tomography (CT) is one of the most efficient clinical diagnostic tools. The main goal of CT is to reproduce an acceptable reconstructed image of an object (either anatomical or functional behaviour) with the help of a limited set of projections at different angles. BACKGROUND: To achieve this goal, one of the most commonly iterative reconstruction algorithm called Maximum Likelihood Expectation Maximization (MLEM) is used. OBJECTIVE: The conventional Maximum Likelihood (ML) algorithm can achieve quality images in CT. However, it still suffers from optimal smoothing as the number of iterations increases. METHODS: For solving this problem, this paper presents a novel statistical image reconstruction algorithm for CT, which utilizes a nonlocal means of fuzzy complex diffusion as a regularization term for noise reduction and edge preservation. RESULTS: The proposed model was evaluated on four test cases phantoms. CONCLUSION: Qualitative and quantitative analyses indicate that the proposed technique has higher efficiency for computed tomography. The proposed method yields significant improvements when compared with the state-of-the-art techniques.

Chronic headache and backache are long-term sequelae of unintentional dural puncture in the obstetric population.

INTRODUCTION: Unintentional dural puncture (UDP) and postdural puncture headache (PDPH) occur during the course of epidural catheter placement for labor analgesia with a reported incidence of 1%-5%. After UDP with an epidural needle, 80%-86% of patients develop PDPH. Acute symptoms after UDP are well known. However, few studies have evaluated the long-term complications of UDP, which is important in assisting parturients in the decision-making informed consent process. We sought to elucidate the long-term (>6 weeks) sequelae of PDPH by examining parturients who had UDP (both recognized and unrecognized) associated with labor epidural analgesia. METHODS: Parturients with a documented UDP (n = 308) over a 5-year period were followed up for acute and long-term residual symptoms (lasting >6 weeks) and compared with a control group (no documented UDP, n = 50) in the same period. Specific symptoms included headache, backache, neck ache, auditory symptoms, and visual symptoms. RESULTS: In comparing parturients with a UDP with control group (no UDP), differences were noted in overall acute symptoms (75.9% vs 21.7%, P < .001), specifically headache (87.0% vs 8.7%, P < .001), backache (47.2% vs 19.6%, P = .002), neck ache (30.1% vs 2.2%, P < .001), auditory (13.8% vs 0%, P = .02), and visual symptoms (19.5% vs 0%, P = .002). Differences were also noted in comparing chronic symptoms (26.5% vs 10.9%, P = .04) and specifically with respect to chronic headache (34.9% vs 2.2%, P < .001), backache (58.1% vs 4.4%, P < .001), and neck ache (14.0% vs 0%, P = .02). No differences were noted between groups in comparing chronic auditory and visual symptoms. CONCLUSION: Chronic headache and backache sequelae persist in the obstetrical population after UDP. When parturients are considering labor epidural analgesia, long-term sequelae should be discussed in the informed consent decision-making process.

Prosthodontic status and needs of elderly institutionalized residents in Mangalore: a prospective study.

AIM: The aim of the present study is to assess the prevalence of Kennedy's classification, status of existing prosthodontic appliances if any, awareness of the subjects regarding various treatment options, and treatment needs in a group of elderly institutionalized residents. MATERIALS AND METHODS: The subjects were selected from various old age homes present in Mangalore city, with ages ranging from 60 to 80 years. The subjects were interviewed and examined by a single trained examiner and findings were recorded on a clinical case history report sheet. RESULTS: Kennedy's class I was most prevalent and class IV the least. Among the subjects examined, only 12.4% were wearing prosthesis. Based on the Nevalainen's index and Karslon's index, most of the prosthodontic appliances were found to be in poor condition. 86% of the subjects were in need of prosthodontic treatment. 75% of the subjects interviewed were unaware of the treatment options available. CONCLUSION: The elderly patients living in institutions do not achieve a deserving and satisfactory oral health care. The oral care assistance in institutionalized elderly patients has been an unfulfilled service.

Epidural catheter placement in morbidly obese parturients with the use of an epidural depth equation prior to ultrasound visualization.

BACKGROUND: Previously, Balki determined the Pearson correlation coefficient with the use of ultrasound (US) was 0.85 in morbidly obese parturients. We aimed to determine if the use of the epidural depth equation (EDE) in conjunction with US can provide better clinical correlation in estimating the distance from the skin to the epidural space in morbidly obese parturients. METHODS: One hundred sixty morbidly obese (≥40 kg/m(2)) parturients requesting labor epidural analgesia were enrolled. Before epidural catheter placement, EDE was used to estimate depth to the epidural space. This estimation was used to help visualize the epidural space with the transverse and midline longitudinal US views and to measure depth to epidural space. The measured epidural depth was made available to the resident trainee before needle insertion. Actual needle depth (ND) to the epidural space was recorded. RESULTS: Pearson's correlation coefficients comparing actual (ND) versus US estimated depth to the epidural space in the longitudinal median and transverse planes were 0.905 (95% CI: 0.873 to 0.929) and 0.899 (95% CI: 0.865 to 0.925), respectively. CONCLUSION: Use of the epidural depth equation (EDE) in conjunction with the longitudinal and transverse US views results in better clinical correlation than with the use of US alone.

Maternal outcomes in women supplemented with a high-protein drink in labour.

BACKGROUND: Because of the potential aspiration risk, oral intake is restricted during labour. AIMS: To determine whether high-protein drink supplementation in labour decreases nausea and emesis and promotes patient satisfaction. MATERIALS AND METHODS: The study was registered with www.clinicaltrials.gov (NCT01414478). Labouring women were randomised into two groups: Group P received a high-protein drink (325 mL) with ice chips/water PRN; and Group C served as control and received only ice chips/water PRN (Study 1). Incidences of nausea and emesis were measured hourly until delivery and at 1 h postdelivery. Patient satisfaction was measured the following day. A secondary aim was to evaluate the rate of gastric emptying (t½ ) in women who ingested either 325 mL of a high-protein drink or ice chips/water (Study 2) using ultrasound. RESULTS: In Study 1, 150 women were recruited (Group P = 75; Group C = 75). There were no differences in the overall incidences of nausea (P = 0.14), emesis (P = 0.15) or in the incidences at the measured time periods (MANOVA, P > 0.05). Median patient satisfaction scores were higher in Group P than in Group C (P = 0.007). In Study 2, 18 additional patients (Group PG = 9; Group CG = 9) were analysed to determine US gastric emptying t½ rates (PG : 25.56 ± 15.90 min [95% CI: 15.17 - 35.94] compared with CG : 20.00 ± 8.70 min [95% CI: 14.34 - 25.66], P = 0.19). CONCLUSION: In labour, patient satisfaction is improved with high-protein drink supplementation compared with ice chips/water with comparable gastric emptying rates.

A 5-year audit of accidental dural punctures, postdural puncture headaches, and failed regional anesthetics at a tertiary-care medical center.

Obstetric anesthesia-related complications occur as a result of labor epidural or spinal placement. The purpose of this continuous quality-improvement audit was to review the occurrence of accidental dural punctures (ADPs), postdural puncture headaches (PDPHs), and failed regional anesthetics at an academic tertiary-care medical center over a 5-year period. Obstetric anesthesia complications contained in three databases consisting of ADPs, PDPHs, and failed regional anesthetics were matched to a perinatal database, with no complications serving as controls. Of the 40,894 consecutive parturients, there were 765 documented complications. Complication rates were 0.73% (95% CI: 0.65-0.82) for ADP, 0.49% (95% CI: 0.43-0.56) for PDPH, and 0.65% (95% CI: 0.57-0.73) for failed regional anesthetic. When compared to the no complication group, factors associated with obstetric anesthesia complications included increased weight and BMI (p < 0.01), epidural block (p < 0.01), and vaginal delivery (p < 0.01).