Diabetes Diagnosis through Machine Learning: An Analysis of Classification Algorithms

Diabetes is a serious and chronic disease characterized by high levels of sugar in the blood. If left untreated, it can lead to numerous complications. In the past, diagnosing diabetes required a visit to a diagnostic center and consultation with a doctor. However, the use of machine learning can help to identify the disease earlier and more accurately. This study aimed to create a model that can accurately predict the likelihood of diabetes in patients using three machine learning classification algorithms: Logistic Regression (LR), Decision Tree (DT), and Naive Bayes (NB). The model was tested on the Pima Indians Diabetes Database (PIDD) from the UCI machine learning repository and the performance of the algorithms was evaluated using various metrics such as accuracy, precision, F-measure, and recall. The results showed that Logistic Regression had the highest accuracy at 71.39% outperforming the other algorithms

RADL: a resource and deadline‑aware dynamic load‑balancer for cloud tasks

Cloud service providers acquire the computing resources and allocate them to their clients. To effectively utilize the resources and achieve higher user satisfaction, efficient task scheduling algorithms play a very pivotal role. A number of task scheduling technique have been proposed in the literature. However, majority of these scheduling algorithms fail to achieve efficient resource utilization that causes them to miss tasks deadlines. This is because these algorithms are not resource and deadline-aware. In this research, a Resource and deadline Aware Dynamic Load-balancer (RADL) for Cloud, tasks have been presented. The proposed scheduling scheme evenly distribute the incoming workload of compute-intensive and independent tasks at run-time. In addition, RADL approach has the capability to accommodate the newly arrived tasks (with shorter deadlines) efficiently and reduce task rejection. The proposed scheduler monitors/updates the task and VM status at run-time. Experimental results show that the proposed technique has attained up to 67.74%, 303.57%, 259.2%, 146.13%, 405.06%, and 259.14% improvement for average resource utilization, meeting tasks deadlines, lower makespan, task response time, penalty cost, and task execution cost respectively as compared to the state-of-the-art tasks scheduling heuristics using three benchmark datasets

Frequency and Outcome of Carotid Atheromatous Disease in Patients With Stroke in Pakistan

Background And Purpose: Limited data exist on the frequency and outcome of carotid artery disease in Pakistan. Such information would help guide the usefulness of screening for the condition in this low-middle income health care setting. Methods: A prospective, descriptive study was conducted among 3 large teaching hospitals in Karachi, Pakistan. Patients referred for carotid Doppler ultrasound examination were included if they had experienced a stroke or TIA within the previous month. The severity and morphology of carotid disease were characterized by trained technicians using standardized criteria. Demographic and risk factor data were collected at baseline, and the outcome of Patients was assessed at least 6 months later. Results: A total of 672 Patients underwent bilateral carotid Doppler ultrasound (1344 carotid examinations). The findings revealed 0% to 50% stenosis in 526 (78%), 51% to 69% stenosis in 57 (8%), 70% to 99% stenosis in 82 (12%), and total occlusion in 7 Patients (1%). Potentially surgically correctable disease, defined as 70% to 99% carotid artery stenosis, was present in only 79 (12%) Patients, of whom 47 (60%) were ipsilateral symptomatic, 15 (20%) asymptomatic, and 17 (20%) had status unknown. Outcome information at \u3e= 6 months follow-up was available for 36 of the 47 (76%) surgically correctable and only 4 of these Patients (12%) had undergone surgical or radiological intervention (carotid endarterectomy in 3 Patients and carotid stenting in 1 Patient). Conclusion: The frequency of carotid artery disease of at least moderate severity is very low in Patients with recent stroke or TIA and there is low utilization of high-cost, carotid intervention procedures in Pakistan. These data raise questions regarding the applicability and cost-effectiveness of routine carotid ultrasound screening in our country and similar population in Asia. The local socio-economic and clinical data do not support routine carotid Doppler ultrasound in every Patient with stroke and TIA in Pakistan. Studies are warranted to determine predictors of significant carotid artery stenosis in stroke/TIA Patients of our country to develop reliable stroke guidelines appropriate for local population

Breast imaging reports for malignant lesions: Are we maintaining recommended BI-RADS® lexicon standards

Background: The purpose of this study was to evaluate mammography reports for diagnosed breast cancer cases in major government and private centers in Karachi, Pakistan, with respect to concordance with the Breast Imaging Reports And Data System (BI-RADS®) lexicon.Methods: A prospective, descriptive, multicenter study was conducted in the radiology sections of the Aga Khan University Hospital, Pakistan Naval Station Shifa Hospital, Advanced Radiology Clinic, Karachi Institute of Radiotherapy and Nuclear Medicine, and Civil Hospital Karachi between May and October 2010 after approval from the ethical review committee of Aga Khan University. Mammograms reported as BI-RADS category 4 and 5 were included in the study. Mammograms reported as BI-RADS category 0, 1, 2 and 3 were excluded. Fifty reports were collected from each center. Data were collected about the clinical indication, breast density, location and description of the lesion, calcification, and comments on axillary lymph nodes. This description was compared with the BI-RADS lexicon.Results: The mean age of the patients was 50 ± 12 years. The clinical indication, breast parenchymal density, lesion location, and presence of calcification were better described by the private centers, while description of lymph node status was better stated by the government centers. This difference was statistically significant, except for lesion description. The description of masses by the two reporting groups was comparable.Conclusion: Mammographic reporting of malignant breast lesions in the private sector is more in line with the BI-RADS lexicon, as compared with government sector hospitals in Karachi, Pakistan. Lymph node documentation was better in government sector reports

Preliminary investigation on properties of novel sustainable composite : fish scales reinforced cement concrete

This study focused on analysing the effect of fish scales reinforcement on fresh and hardened-state properties of concrete. For this purpose, 24 cubes and 24 cylinders were casted at a design mix ratio of 1:2.3:4.3. The water-cement ratio of 0.57 was maintained. The fish scales reinforcement levels of 0%, 1%, 1.5% and 2% by weight of cement were maintained for casting of specimens. For fresh-state assessment, the workability of concrete mixes was observed by slump test and the results showed that, with the addition of fish scales, the slump value decreased due to increase in water demand. With the addition of 2% Fish Scales, the workability of concrete mixes reduced by 36.40%. The compressive strength and tensile strength of concrete cubes and cylinders were tested with Universal Testing Machine (UTM) at curing period of 7 and 28 days. Out of 48 specimens casted, a total of 24 specimens were subjected to compressive strength test while other 24 specimens were tested for tensile strength. The results reported that with addition of 2% fish scales in concrete, the tensile strength of concrete increased but the compressive strength initially decreased and later increased. It can thus be concluded that the fish scales can be incorporated in concrete with steel to enhance the tensile strength of concrete. Keeping the initial decrease in compressive strength of concrete in consideration, it can be recommended that the fish scale reinforced concrete can be safely used in light weight structures and non-structural elements like floor slabs and ribs

The Karachi intracranial stenosis study (KISS) Protocol: an urban multicenter case-control investigation reporting the clinical, radiologic and biochemical associations of intracranial stenosis in Pakistan.

Background: Intracranial stenosis is the most common cause of stroke among Asians. It has a poor prognosis with a high rate of recurrence. No effective medical or surgical treatment modality has been developed for the treatment of stroke due to intracranial stenosis. We aim to identify risk factors and biomarkers for intracranial stenosis and to develop techniques such as use of transcranial doppler to help diagnose intracranial stenosis in a cost-effective manner. Methods/Design: The Karachi Intracranial Stenosis Study (KISS) is a prospective, observational, case-control study to describe the clinical features and determine the risk factors of patients with stroke due to intracranial stenosis and compare them to those with stroke due to other etiologies as well as to unaffected individuals. We plan to recruit 200 patients with stroke due to intracranial stenosis and two control groups each of 150 matched individuals. The first set of controls will include patients with ischemic stroke that is due to other atherosclerotic mechanisms specifically lacunar and cardioembolic strokes. The second group will consist of stroke free individuals. Standardized interviews will be conducted to determine demographic, medical, social, and behavioral variables along with baseline medications. Mandatory procedures for inclusion in the study are clinical confirmation of stroke by a healthcare professional within 72 hours of onset, 12 lead electrocardiogram, and neuroimaging. In addition, lipid profile, serum glucose, creatinine and HbA1C will be measured in all participants. Ancillary tests will include carotid ultrasound, transcranial doppler and magnetic resonance or computed tomography angiogram to rule out concurrent carotid disease. Echocardiogram and other additional investigations will be performed at these centers at the discretion of the regional physicians. Discussion: The results of this study will help inform locally relevant clinical guidelines and effective public health and individual interventions

Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described

INTEGRATION AND IMPLEMENTATION OF PRECISION MEDICINE IN THE MULTIFACETED INFLAMMATORY BOWEL DISEASE

<p><i>Background: Inflammatory Bowel Disease (IBD) represents a multifaceted group of disorders that demand precise and personalized approaches to diagnosis and treatment. </i></p><p><i>Methods: A retrospective cohort study was conducted, involving 220 patients diagnosed with IBD. Genetic and genomic analysis, immunological profiling, and assessment of environmental and lifestyle factors were performed. Inclusion criteria ensured the selection of a relevant patient population, while ethical considerations were upheld throughout data collection.</i></p><p><i>Results: Genetic analysis identified significant single-nucleotide polymorphisms (SNPs) associated with IBD susceptibility, emphasizing the genetic complexity of the disease. Immunological profiling revealed elevated pro-inflammatory cytokine levels, underlining the role of the immune system in IBD. Environmental factors, including dietary habits and geographical location, demonstrated associations with IBD risk.</i></p><p><i>Conclusion: The integration of precision medicine in IBD management offers personalized approaches to diagnosis and treatment. While these results are hypothetical, they underscore the need for further research and the potential for tailored interventions to improve IBD outcomes.</i></p&gt

GA-IRACE: Genetic Algorithm-Based Improved Resource Aware Cost-Efficient Scheduler for Cloud Fog Computing Environment

The ever-growing number of Internet of Things (IoT) devices increases the amount of data produced on daily basis. To handle such a massive amount of data, cloud computing provides storage, processing, and analytical services. Besides this, real-time applications, i.e., online gaming, smart traffic management, and smart healthcare, cannot tolerate the high latency and bandwidth consumption. The fog computing paradigm brings the cloud services closer to the network edge to provide quality of service (QoS) to such applications. However, efficient task scheduling becomes critical for improving the performance due to the heterogeneous nature, resource-constrained, and distributed environment of fog resources. With an efficient task scheduling algorithm, the response time to application requests can be reduced along with bandwidth and cloud resource costs. This paper presents a genetic algorithm-based solution to find an efficient scheduling approach for mapping application modules in a cloud fog computing environment. Our proposed solution is based on the execution time as a fitness function to determine an efficient module scheduling on the available fog devices. The proposed approach has been evaluated and compared against baseline algorithms in terms of execution time, monetary cost, and bandwidth. Comprehensive simulation results show that the proposed approach offers a better scheduling strategy than the existing scheduler