A5100629741- Artificial Intelligence in Healthcare
- Machine Learning in Healthcare
- Plant Physiology and Cultivation Studies
- Cutaneous Melanoma Detection and Management
- Nonmelanoma Skin Cancer Studies
- Postharvest Quality and Shelf Life Management
- Disaster Management and Resilience
- Seed and Plant Biochemistry
- Genetic diversity and population structure
- Renal and Vascular Pathologies
- Irrigation Practices and Water Management
- AI in cancer detection
- Cerebrovascular and Carotid Artery Diseases
- COVID-19 diagnosis using AI
- Acute Ischemic Stroke Management
- Plant Virus Research Studies
- Advances in Cucurbitaceae Research
- Disaster Response and Management
Leading University
2022-2024
University of Asia Pacific
2023
Bangladesh Agricultural Research Institute
2019
Kansas City VA Medical Center
2015
The risk evaluation of natural disasters is an obstacle to ensuring healthcare services during catastrophic events worldwide. Therefore, timely and appropriate environmental health essential. In this study, we incorporated the information from databases such as PubMed, Google Scholar, Scopus. We performed study explore feasibility using artificial intelligence (AI) in disaster emergency management. Natural have some phenomenon that bound happen. So, can use AI inform authorities about risks...
Chronic kidney disease (CKD) represents a significant global health challenge characterized by progressive decline in renal function, leading to the accumulation of waste products and disruptions fluid balance within body. Given its pervasive impact on public health, there is pressing need for effective diagnostic tools enable timely intervention. Our study delves into application cutting-edge transfer learning models early detection CKD. We carefully test performance several models, such as...
Information about genetic variation has become more critical and deciding factor for any breeding improvement effort,is difficult inefficient inaccurate when based on morphological traits only. Therefore, this investigation was conducted using nine microsatellite DNA markers to evaluate among 96 muskmelon germplasm in Bangladesh. All were polymorphic. Lower values detected observed than expected heterozygosity all loci, indicating homozygous condition the sample population. A total number of...
Nineteen genotypes of mango including nine released varieties viz. BARI Aam-1, Aam-2 (Laxmanbhog), Aam-3, Aam- 4 (Hybrid), Aam-5, Aam-6, Aam-7, Aam-8, Aam-9; one parental line M- 3896 and Geographical Indication Crops (GIs) Haribhanga, Surjapuri, Fazli, Gourmoti, Ashwina, Khirsapat, Gopalbhog, Langra Ranipasand were characterized with a view to identifying the degree morphological molecular variation within their historical background background, establish permanent database for...
Chronic Kidney Disease (CKD) represents a significant global health challenge, characterized by the progressive decline in renal function, leading to accumulation of waste products and disruptions fluid balance within body. Given its pervasive impact on public health, there is pressing need for effective diagnostic tools enable timely intervention. Our study delves into application cutting-edge transfer learning models early detection CKD. Leveraging comprehensive publicly available dataset,...
Kidneys are the filter of human body. About 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> global population is thought to be affected by Chronic Kidney Disease (CKD), which causes kidney function decline. To protect in danger patients from additional damage, effective risk evaluation CKD and appropriate monitoring crucial. Due quick precise detection capabilities, Machine Learning models can help practitioners accomplish this goal...
OBJECTIVE: To determine common risk factors and etiologies of stroke in young patients to promote better primary secondary prevention this age group. BACKGROUND: Stroke the is a devastating disease, producing significant morbidity mortality. We investigated first ever recurrent 18-50 years old. DESIGN/METHODS: Retrospective data from 560 aged with was analyzed over ten year period (2003-2013). Data obtained Neurology department large tertiary care. Presence were identified amongst...