Domain-Specific Deep Learning Feature Extractor for Diabetic Foot Ulcer Detection

Diabetic Foot Ulcer (DFU) is a condition requiring constant monitoring and evaluations for treatment. DFU patient population is on the rise and will soon outpace the available health resources. Autonomous monitoring and evaluation of DFU wounds is a much-needed area in health care. In this paper, we evaluate and identify the most accurate feature extractor that is the core basis for developing a deep-learning wound detection network. For the evaluation, we used mAP and F1-score on the publicly available DFU2020 dataset. A combination of UNet and EfficientNetb3 feature extractor resulted in the best evaluation among the 14 networks compared. UNet and Efficientnetb3 can be used as the classifier in the development of a comprehensive DFU domain-specific autonomous wound detection pipeline.Comment: 5 pages, 2 figures, 3 tables, 2022 IEEE International Conference on Data Mining Workshop

Development of an indigenous screening instrument in Pakistan: the Aga Khan University Anxiety and Depression Scale

The use of translations of instruments for detecting anxiety and depression continues to be debated. An indigenous screening instrument has been developed in Urdu for anxiety-depression syndromes at the Aga Khan University. It has been developed from the complaints of 150 anxious and depressed patients presenting to a non-speciality clinic and has been validated in 53 patients in a psychiatry clinic. The questionnaire has 25 items, 13 psychlogical and 12 somatic. At a score of 20 it has a sensitivity of 66%, a specificity of 79%, a positive predictive value of 83 and a negative predictive value of 60. In comparison with available instruments in Urdu, comprising of either psychological or somatic items, this scale includes both, which increases its reliability for use as a screening instrument by Community Health Workers in a primary health care setting, in epidemiologic work in Pakistan and in transcultural psychiatric research

Low Power Data Acquisition System for Bioimplantable Devices

Signal acquisition represents the most important block in biomedical devices, because of its responsibilities to retrieve precise data from the biological tissues. In this paper an energy efficient data acquisition unit is presented which includes low power high bandwidth front-end amplifier and a 10-bit fully differential successive approximation ADC. The proposed system is designed with 0.18 µm CMOS technology and the simulation results show that the bioamplifier maintains a wide bandwidth versus low noise trade-off and the proposed SAR-ADC consumes 450 nW power under 1.8 V supply and retain the effective number of bit 9.55 in 100 KS/s sampling rate

Synthesizing Diabetic Foot Ulcer Images with Diffusion Model

Diabetic Foot Ulcer (DFU) is a serious skin wound requiring specialized care. However, real DFU datasets are limited, hindering clinical training and research activities. In recent years, generative adversarial networks and diffusion models have emerged as powerful tools for generating synthetic images with remarkable realism and diversity in many applications. This paper explores the potential of diffusion models for synthesizing DFU images and evaluates their authenticity through expert clinician assessments. Additionally, evaluation metrics such as Frechet Inception Distance (FID) and Kernel Inception Distance (KID) are examined to assess the quality of the synthetic DFU images. A dataset of 2,000 DFU images is used for training the diffusion model, and the synthetic images are generated by applying diffusion processes. The results indicate that the diffusion model successfully synthesizes visually indistinguishable DFU images. 70% of the time, clinicians marked synthetic DFU images as real DFUs. However, clinicians demonstrate higher unanimous confidence in rating real images than synthetic ones. The study also reveals that FID and KID metrics do not significantly align with clinicians' assessments, suggesting alternative evaluation approaches are needed. The findings highlight the potential of diffusion models for generating synthetic DFU images and their impact on medical training programs and research in wound detection and classification.Comment: 8 pages, 3 figures, 6th Workshop on AI for Aging, Rehabilitation and Intelligent Assisted Living at European Conference on Machine Learning, Italy, 202

Numerical simulation of periodic MHD casson nanofluid flow through porous stretching sheet

The perspective of this paper is to characterize a Casson type of Non-Newtonian fluid flow through heat as well as mass conduction towards a stretching surface with thermophoresis and radiation absorption impacts in association with periodic hydromagnetic effect. Here heat absorption is also integrated with the heat absorbing parameter. A time dependent fundamental set of equations, i.e. momentum, energy and concentration have been established to discuss the fluid flow system. Explicit finite difference technique is occupied here by executing a procedure in Compaq Visual Fortran 6.6a to elucidate the mathematical model of liquid flow. The stability and convergence inspection has been accomplished. It has observed that the present work converged at, Pr ≥ 0.447 indicates the value of Prandtl number and Le ≥ 0.163 indicates the value of Lewis number. Impact of useful physical parameters has been illustrated graphically on various flow fields. It has inspected that the periodic magnetic field has helped to increase the interaction of the nanoparticles in the velocity field significantly. The field has been depicted in a vibrating form which is also done newly in this work. Subsequently, the Lorentz force has also represented a great impact in the updated visualization (streamlines and isotherms) of the flow field. The respective fields appeared with more wave for the larger values of magnetic parameter. These results help to visualize a theoretical idea of the effect of modern electromagnetic induction use in industry instead of traditional energy sources. Moreover, it has a great application in lung and prostate cancer therapy

Experimental investigation on compression ignition engine powered with pentanol and thevetia peruviana methyl ester under reactivity controlled compression ignition mode of operation

In the current study, an effort is carried out to study the influence of pentanol as low reactive fuel (LRF) along with diesel and Thevetia peruviana methyl ester (TPME) as high reactive fuels (HRF) in reactivity controlled compression ignition (RCCI) engine. The experiments are conducted on dual fuel engine at 50% load for RCCI mode of operation by varying pentanol percentage in injected fuels. The results revealed that RCCI mode of operation at 10% of pentanol in injected fuels exhibited higher brake thermal efficiency (BTE) of 22.15% for diesel and pentanol fuel combination, which is about 9.1% and 27.3% higher than other B20 and pentanol, B100 and pentanol fuel combinations respectively. As the percentage of pentanol increased in injected fuels, hydrocarbon (HC) and carbon monoxide (CO) emissions are increased while nitrogen oxide (NOx) and smoke emissions are decreased. Among various fuel combinations tested diesel and pentanol fuel combination gives lower HC, CO and smoke emissions and higher NOx emissions. At 10% pentanol in injected fuels, the highest heat release rate (HRR) and in-cylinder pressure are found for diesel and pentanol fuel combinations compared with other fuels

In Vivo Characterization of a Wireless Telemetry Module for a Capsule Endoscopy System Utilizing a Conformal Antenna

This paper describes the design, fabrication, packaging, and performance characterization of a conformal helix antenna created on the outside of a 10 mm ×30 mm capsule endoscope designed to operate at a carrier frequency of 433 MHz within human tissue. Wireless data transfer was established between the integrated capsule system and an external receiver. The telemetry system was tested within a tissue phantom and in vivo porcine models. Two different types of transmission modes were tested. The first mode, replicating normal operating conditions, used data packets at a steady power level of 0 dBm, while the capsule was being withdrawn at a steady rate from the small intestine. The second mode, replicating the worst-case clinical scenario of capsule retention within the small bowel, sent data with stepwise increasing power levels of –10, 0, 6, and 10 dBm, with the capsule fixed in position. The temperature of the tissue surrounding the external antenna was monitored at all times using thermistors embedded within the capsule shell to observe potential safety issues. The recorded data showed, for both modes of operation, a low error transmission of 10−3 packet error rate and 10−5 bit error rate and no temperature increase of the tissue according to IEEE standards

A clinical study of arrhythmias associated with acute coronary syndrome: a hospital based study of a high risk and previously undocumented population

Background: ACS represents a global epidemic. Arrhythmia in ACS is common. Careful investigation may lead to further improvement of prognosis. Retrospectively analyzed the year- round data of our center. Study was undertaken to analyze the incidence, frequency and type of arrhythmias in ACS. This is to aid timely intervention and to modify the outcome. Identification of the type of arrhythmia is of therapeutic and prognostic importance.Methods: This cross sectional analytical study was conducted in the Department of Cardiology, Apollo Hospitals Dhaka, from January 2019 to January 2020 with ACS patients. Enrolled consecutively and data analyzed.Results: There were 500 patients enrolled considering inclusion and exclusion criteria. Sample was subdivided into 3 groups on the type of ACS. Group-I with UA, Group-II with NSTE - ACS and Group-III with STE - ACS. Different types of arrhythmia noted. Types of arrhythmia were correlated with type of ACS. 500 patients included. Mean age 55.53±12.70, 71.6% male and 28.4% female. 60.4% hypertensive, 46.2% diabetic, 20.2% positive family history of CAD, 32.2% current smoker, 56.4% dyslipidaemic and 9.6% asthmatic. 31.2% UA, 39.2% NSTE-ACS and 29.6% STE-ACS. Type of arrhythmias noted. 22% sinus tachycardia, 20.2% sinus bradycardia, 9% atrial fibrillation, 5.2% ventricular ectopic, 4.8% supra ventricular ectopic, 2.8% bundle branch block, 2.2% atrio-ventricular block, 1% broad complex tachycardia, 0.4% narrow complex tachycardia, 0.2% sinus node dysfunction and 32.2% without any arrhythmia. Significant incidences of arrhythmia detected - respectively 29.8%, 39.2% and 31%, p<0.001.Conclusions: In conclusion, arrhythmias in ACS are common. More attention should be paid to improve their treatment and prognosis

Global, regional, and national burden of chronic kidney disease, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Health system planning requires careful assessment of chronic kidney disease (CKD) epidemiology, but data for morbidity and mortality of this disease are scarce or non-existent in many countries. We estimated the global, regional, and national burden of CKD, as well as the burden of cardiovascular disease and gout attributable to impaired kidney function, for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017. We use the term CKD to refer to the morbidity and mortality that can be directly attributed to all stages of CKD, and we use the term impaired kidney function to refer to the additional risk of CKD from cardiovascular disease and gout. Methods The main data sources we used were published literature, vital registration systems, end-stage kidney disease registries, and household surveys. Estimates of CKD burden were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool, and included incidence, prevalence, years lived with disability, mortality, years of life lost, and disability-adjusted life-years (DALYs). A comparative risk assessment approach was used to estimate the proportion of cardiovascular diseases and gout burden attributable to impaired kidney function. Findings Globally, in 2017, 1·2 million (95% uncertainty interval [UI] 1·2 to 1·3) people died from CKD. The global all-age mortality rate from CKD increased 41·5% (95% UI 35·2 to 46·5) between 1990 and 2017, although there was no significant change in the age-standardised mortality rate (2·8%, −1·5 to 6·3). In 2017, 697·5 million (95% UI 649·2 to 752·0) cases of all-stage CKD were recorded, for a global prevalence of 9·1% (8·5 to 9·8). The global all-age prevalence of CKD increased 29·3% (95% UI 26·4 to 32·6) since 1990, whereas the age-standardised prevalence remained stable (1·2%, −1·1 to 3·5). CKD resulted in 35·8 million (95% UI 33·7 to 38·0) DALYs in 2017, with diabetic nephropathy accounting for almost a third of DALYs. Most of the burden of CKD was concentrated in the three lowest quintiles of Socio-demographic Index (SDI). In several regions, particularly Oceania, sub-Saharan Africa, and Latin America, the burden of CKD was much higher than expected for the level of development, whereas the disease burden in western, eastern, and central sub-Saharan Africa, east Asia, south Asia, central and eastern Europe, Australasia, and western Europe was lower than expected. 1·4 million (95% UI 1·2 to 1·6) cardiovascular disease-related deaths and 25·3 million (22·2 to 28·9) cardiovascular disease DALYs were attributable to impaired kidney function. Interpretation Kidney disease has a major effect on global health, both as a direct cause of global morbidity and mortality and as an important risk factor for cardiovascular disease. CKD is largely preventable and treatable and deserves greater attention in global health policy decision making, particularly in locations with low and middle SDI