A Five-Year Trend Analysis of Antibacterial Resistance Patterns Among Non-fermenting Gram-Negative Bacilli: A Retrospective Study From the ICU Settings of a Tertiary Care Hospital.

Introduction: Non-fermenting gram-negative bacilli (NFGNB) infections have emerged as a serious health concern in ICUs. Multi-drug resistant (MDR) strains of NFGNB can evolve by acquiring resistance genes to at least one agent in three or more antibacterial categories. This study aimed to analyse the prevalence of NFGNB, the distribution of MDR strains, and antibiotic resistance trends of NFGNB in different ICUs of a tertiary care hospital over a period of five years.

Computational analysis of human gut microbial prolyl oligopeptidases (POPs) reveal candidate genes as therapeutics for celiac disease.

Celiac disease (CD) is a common autoimmune disorder in which the patients are unable to digest gluten, which is present in foods made up of wheat, barley and rye. Whilst diagnosis happens late in 80% of the cases, avoidance of such foods appears to be the common solution. Alternative management strategies are required for the patients and their families since CD is also genetically carried over.

Unravelling the signatures of submarine groundwater discharge and seawater intrusion along the coastal plains of Odisha, India: a multi-proxy approach.

Submarine Groundwater Discharge (SGD) and Seawater Intrusion (SWI) are two contrary hydrological processes that occur across the land-sea continuum and understanding their nature is essential for management and development of coastal groundwater resource. Present study has attempted to demarcate probable zones of SGD and SWI along highly populated Odisha coastal plains which is water stressed due to indiscriminate-exploitation of groundwater leading to salinization and fresh groundwater loss from the alluvial aquifers. A multi-proxy investigation approach including decadal groundwater level dynamics, LANDSAT derived sea surface temperature (SST) anomalies and in-situ physicochemical analysis (pH, EC, TDS, salinity and temperature) of porewater, groundwater and seawater were used to locate the SGD and SWI sites.

Correlation Between Radiological and Functional Outcomes Following Operative and Nonoperative Management of Acetabular Fractures: A Prospective Observational Study.

Introduction: The management of acetabular fractures is a complicated orthopedic procedure that has been advancing with time. Newer radiological tools like CT scans help surgeons to identify and manage these fractures more attentively. The study was conducted to evaluate the clinical and radiographic outcomes in patients with acetabular fractures managed either conservatively or by open reduction and internal fixation.

BT-CNN: a balanced binary tree architecture for classification of brain tumour using MRI imaging.

Deep learning is a very important technique in clinical diagnosis and therapy in the present world. Convolutional Neural Network (CNN) is a recent development in deep learning that is used in computer vision. Our medical investigation focuses on the identification of brain tumour.

Stroke incidence, mortality, subtypes in rural and urban populations in five geographic areas of India (2018-2019): results from the National Stroke Registry Programme.

Background: Increasing stroke burden in India demands a long-term stroke surveillance framework. Earlier studies in India were urban-based, short term and provided limited data on stroke incidence and its outcomes. This gap is addressed by the establishment of five population-based stroke registries (PBSRs) of the National Stroke Registry Programme, India.

Detection of COVID-19 using edge devices by a light-weight convolutional neural network from chest X-ray images.

Deep learning is a highly significant technology in clinical treatment and diagnostics nowadays. Convolutional Neural Network (CNN) is a new idea in deep learning that is being used in the area of computer vision. The COVID-19 detection is the subject of our medical study.

Examining the rural-urban differentials in yoga and mindfulness practices among middle-aged and older adults in India: secondary analysis of a national representative survey.

Physical activity and mental well-being play an important role in reducing the risk of various diseases and in promoting independence among older adults. Appropriate physical activity, including yoga and mindfulness practices, can help rectify the loss of independence due to aging and have a positive influence on physical health and functional activities. This study assessed rural-urban differences in yoga and mindfulness practices and their associated factors among middle-aged and older Indian adults.

The Pattern of Health-Seeking Behavior among Juang Tribe- A Particularly Vulnerable Tribal Group of Odisha, India.

Introduction: Social and economic position, environment, access to healthcare, ethos, and worldview are all important determinants of people's health-seeking behavior. Tribal communities in India oscillate between their emic rationale for the cause and treatment of health concerns on the one hand and affordable modern methods on the other. The present article is based on a study conducted among the Junag tribe of Odisha to understand their acceptance and preference for traditional or modern healthcare systems and the reasons for these choices.

A new efficient referential genome compression technique for FastQ files.

Hospitals and medical laboratories create a tremendous amount of genome sequence data every day for use in research, surgery, and illness diagnosis. To make storage comprehensible, compression is therefore essential for the storage, monitoring, and distribution of all these data. A novel data compression technique is required to reduce the time as well as the cost of storage, transmission, and data processing.

DMF-Net: a deep multi-level semantic fusion network for high-resolution chest CT and X-ray image de-noising.

Medical images such as CT and X-ray have been widely used for the detection of several chest infections and lung diseases. However, these images are susceptible to different types of noise, and it is hard to remove these noises due to their complex distribution. The presence of such noise significantly deteriorates the quality of the images and significantly affects the diagnosis performance.

Impacts of climate change and coastal salinization on the environmental risk of heavy metal contamination along the odisha coast, India.

Climate change-mediated rise in sea level and storm surges, along with indiscriminate exploitation of groundwater along populous coastal regions have led to seawater intrusion. Studies on groundwater salinization and heavy metal contamination trends are limited. Present study investigated the heavy metal contamination, associated risks and provided initial information on the impacts of groundwater salinization on heavy metals along the coastal plains of Odisha, India.

Factors associated with poor self-rated health among chronic kidney disease patients and their health care utilization: Insights from LASI wave-1, 2017-18.

Background: Chronic kidney disease (CKD), associated with other chronic conditions affects the physical, behavioral, and psychological aspects of an individual, leading to poor self-rated health. Hence, we aimed to assess the factors associated with poor self-rated health (SRH) in CKD patients. Additionally, we assessed their health care utilization.

Automated Detection and Segmentation of Exudates for the Screening of Background Retinopathy.

Exudate, an asymptomatic yellow deposit on retina, is among the primary characteristics of background diabetic retinopathy. Background diabetic retinopathy is a retinopathy related to high blood sugar levels which slowly affects all the organs of the body. The early detection of exudates aids doctors in screening the patients suffering from background diabetic retinopathy.

Prevalence and pattern of multimorbidity among chronic kidney disease patients: a community study in chronic kidney disease hotspot area of Eastern India.

Introduction: Chronic kidney disease (CKD) is mostly asymptomatic until reaching an advanced stage. Although conditions such as hypertension and diabetes can cause it, CKD can itself lead to secondary hypertension and cardiovascular disease (CVD). Understanding the types and prevalence of associated chronic conditions among CKD patient could help improve screening for early detection and case management.

An Efficient Deep Learning Method for Detection of COVID-19 Infection Using Chest X-ray Images.

The research community has recently shown significant interest in designing automated systems to detect coronavirus disease 2019 (COVID-19) using deep learning approaches and chest radiography images. However, state-of-the-art deep learning techniques, especially convolutional neural networks (CNNs), demand more learnable parameters and memory. Therefore, they may not be suitable for real-time diagnosis.

A Deep Intelligent Attack Detection Framework for Fog-Based IoT Systems.

Fog computing provides a multitude of end-based IoT system services. End IoT devices exchange information with fog nodes and the cloud to handle client undertakings. During the process of data collection between the layer of fog and the cloud, there are more chances of crucial attacks or assaults like DDoS and many more security attacks being compromised by IoT end devices.

Enhanced framework for COVID-19 prediction with computed tomography scan images using dense convolutional neural network and novel loss function.

Recent studies have shown that computed tomography (CT) scan images can characterize COVID-19 disease in patients. Several deep learning (DL) methods have been proposed for diagnosis in the literature, including convolutional neural networks (CNN). But, with inefficient patient classification models, the number of 'False Negatives' can put lives at risk.

A novel service robot assignment approach for COVID-19 infected patients: a case of medical data driven decision making.

Coronavirus Disease-19 (COVID-19) is a major concern for the entire world in the current era. Coronavirus is a very dangerous infectious virus that spreads rapidly from person to person. It spreads in exponential manner on a global scale.

GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force.

Walking (gait) irregularities and abnormalities are predictors and symptoms of disorder and disability. In the past, elaborate video (camera-based) systems, pressure mats, or a mix of the two has been used in clinical settings to monitor and evaluate gait. This article presents an artificial intelligence-based comprehensive investigation of ground reaction force (GRF) pattern to classify the healthy control and gait disorders using the large-scale ground reaction force.

HTLML: Hybrid AI Based Model for Detection of Alzheimer's Disease.

Alzheimer's disease (AD) is a degenerative condition of the brain that affects the memory and reasoning abilities of patients. Memory is steadily wiped out by this condition, which gradually affects the brain's ability to think, recall, and form intentions. In order to properly identify this disease, a variety of manual imaging modalities including CT, MRI, PET, etc.

Design of Smart and Secured Healthcare Service Using Deep Learning with Modified SHA-256 Algorithm.

Background: The modern era of human society has seen the rise of a different variety of diseases. The mortality rate, therefore, increases without adequate care which consequently causes wealth loss. It has become a priority of humans to take care of health and wealth in a genuine way.

An Enhanced Transfer Learning Based Classification for Diagnosis of Skin Cancer.

Skin cancer is the most commonly diagnosed and reported malignancy worldwide. To reduce the death rate from cancer, it is essential to diagnose skin cancer at a benign stage as soon as possible. To save lives, an automated system that can detect skin cancer in its earliest stages is necessary.

Neonatal Joubert Syndrome With Renal Involvement and Respiratory Distress.

Joubert syndrome (JS) is a rare autosomal recessive neurodevelopmental disorder with characteristic clinical presentation of hyperpnea-apnea spells, hypotonia, dysmorphic facies, and nystagmus and imaging features of molar tooth sign and cerebellar vermian hypoplasia-dysplasia. Early diagnosis is needed for timely management and favorable outcome. We present a case of neonatal JS with renal involvement presenting with respiratory distress and highlight the characteristic clinical and imaging findings.