
Prabha SrinivasagamMayo Clinic Health System · Department of Plastic Surgery
Prabha Srinivasagam
Doctor of Philosophy
Artificial Intelligence, Large Language Model, Machine Learning, Medical Imaging
About
44
Publications
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Introduction
Currently, I am working in Artificial Intelligence and Large Language Model
Publications
Publications (44)
In this work, an attempt has been made to perform asymmetry analysis in breast thermograms using non-linear total variation diffusion filter and reaction diffusion based level set method. Breast images used in this study are obtained from online database of the project PROENG. Initially the images are subjected to total variation (TV) diffusion fil...
Artificial intelligence (AI) is not merely a tool for the future of clinical medicine; it is already reshaping the landscape, challenging traditional paradigms, and expanding the horizons of what is achievable in healthcare [...]
Current clinical care relies heavily on complex, rule-based systems for tasks like diagnosis and treatment. However, these systems can be cumbersome and require constant updates. This study explores the potential of the large language model (LLM), LLaMA 2, to address these limitations. We tested LLaMA 2’s performance in interpreting complex clinica...
Background: Effective pain management is crucial for both comfort and outcomes, yet predicting and managing this pain is difficult. This study aimed to analyze postoperative pain in patients undergoing hand surgery at the Mayo Clinic Florida, examining how patient characteristics and anxiety affect pain outcomes. Methods: We conducted a single-arm...
Background
Addressing language barriers through accurate interpretation is crucial for providing quality care and establishing trust. While the ability of artificial intelligence (AI) to translate medical documentation has been studied, its role for patient-provider communication is less explored. This review evaluates AI’s effectiveness in clinica...
The marine benthic zone is host to a vast array of species that are vital to both ecosystem function and biodiversity conservation. Understanding these underwater communities is essential for ecological research, conservation efforts, and sustainable resource management. However, traditional surveying techniques face significant challenges in the u...
MRI is the most influential and flexible tool used for the diagnosis of various pathological alterations of living tissues. Identification of structural abnormalities in brain has become a rising attention for the early prediction and diagnosis of schizophrenia from the healthy controls. Recognizing the biomarkers in schizophrenic patients and rela...
MRI is the most influential and flexible tool used Magnetic Resonant Imaging techniques is the prominent method for understanding the neurophysiological changes occurred in the brain for the efficient diagnosis and classification of Alzheimers. Alzheimers is the memory related disease which commonly occurred in the age group of 45–65. Hippocampal r...
Alzheimer’s disease (AD) is a frequent form of dementia that primarily affects elderly individuals. In clinical practice, it has been a challenge to identify AD in its early stages. Currently, there is no cure for AD, and no biomarker has been identified that is accurate in early AD detection either. Moreover, clinical studies for AD medications ha...
Bioinformatics is defined as the application of tools, computation, analysis to capture the bioactivity data and interpretation of biological data. To develop or to discover the drug, the biological information of proteins, cells, RNA’S, DNA is required to analyze those functional behavior of compounds structures, physical and chemical properties....
Segmentation is necessary for dental images for finding the parts of the teeth, surrounding tissues, and bones. The human identification system in dental methodology is a tedious and time-consuming process. The automatic identification system is the best solution for dental diagnosis and dental treatment systems. Choosing an appropriate region of i...
This paper contains a brief discussion about Diabetic Retinopathy. As the name indicates, it’s a medical complication present in diabetic patients which affects the retina. Diabetic Retinopathy acronymed as DR is a medical circumstance where the high glucose levels in the blood start affecting the blood vessels in the retina. The paper discusses th...
Background:
The importance of identifying the structural and functional abnormalities in the brain in early prediction and diagnosis of schizophrenia has grabbed the attention of both the neuroimaging scientist and clinician.
Objective:
The purpose of this study is to structure a review paper that find out the condition and recognize specific bi...
Background
Alzheimer’s disease (AD) is associated with Dementia, and it is also a memory syndrome in the brain. It affects the brain tissues and causes major changes in day-to-day activities. Aging is a major cause of Alzheimer's disease. AD is characterized by two pathological hallmarks as, Amyloid β protein and neurofibrillary tangles of hyperpho...
Purpose study: Alzheimer is a type of dementia that usually affects older adults by creating memory loss due to damaged brain cells. The damaged brain cells lead to shrinkage in the size of the brain and it is very difficult to extract the grey matter (GM) and white matter (WM). The segmentation of GM and WM is a challenging task due to its homogen...
Nature-inspired algorithms play a vital role in various applications, namely image processing, engineering, industrialized designs and business. Generally, these algorithms are inspired by the nature which is helpful in segmenting the brain internal regions, namely cerebrospinal fluid, grey matter HC, white matter, ventricle and so on. Segmentation...
Thermal pattern which shows asymmetry plays a vital role to diagnosis the cancer in breast thermogram. In this work, asymmetrical pattern of thermal images is analysed using coherence-enhanced diffusion filtering (CEDF)-based reaction diffusion level set and Curvelet transform (CT). The breast tissues are segmented using reaction diffusion level se...
Breast cancer is the second leading cause of cancer death among women preceded by cervix cancer. It has been reported that at the early stage of detection there is 85% of chance of getting cured whereas only 10% of chance at later stage diagnosis. The current screening modalities are expensive, intricate imaging measures and unhealthy from radiatio...
Automatic segmentation of brain sub regions such as White Matter (GM), Corpus Callosum (CC), Grey Matter (WM) and Hippocampus (HC) is a challenging task due to the variations in the structure of the brain. The development of an automation process will help in identifying the Alzheimer disease (AD). The maximum distinctive AD related to neuronal los...
The image noise removal and restoration techniques invariably employ the hybrid filter and genetic algorithm approaches for recovery of noise free images. However, the desired level of denoising is not met with these approaches. The usage of adaptive genetic algorithm recovers the quality of the restored image. In order to improve the image denoisi...
Segmentation is necessary for dental images for finding the parts of the teeth, surrounding tissues, and bones. The human identification system in dental methodology is a tedious and time-consuming process. The automatic identification system is the best solution for dental diagnosis and dental treatment systems. Choosing an appropriate region of i...
Clustering analysis of medical infrared images is found to be very effective for extracting local information, which helps to identify the abnormalities associated with region of interest. Breast tissue extraction in breast thermograms is challenging due to its low signal-to-noise ratio, low contrast and absence of clear edges. Accurate detection o...
Asymmetry analysis of thermal images plays a prominent role in automated diagnosis of normal and abnormal breast tissues. Accurate segmentation of breast tissues further enhances the analysis. In this work, asymmetry analysis of breast thermal images is carried out using efficient fractal algorithm. Prior to feature extraction, the breast tissues a...
In this work, an attempt is made to segment and analyse the breast tissue using bilateral filter and Distance Regularized Level Set Evolution (DRLSE) method. Breast thermal images are obtained from online database PROENG. The noise due to sensors and circuits during acquisition in the breast images are reduced using bilateral filter integrated with...
Background:
Breast thermography is a potential imaging method for the early detection of breast cancer. The pathological conditions can be determined by measuring temperature variations in the abnormal breast regions. Accurate delineation of breast tissues is reported as a challenging task due to inherent limitations of infrared images such as low...
The health impact of retinoic acid (All Trans Retinoic Acid; ATRA) in the development of lung pathology and tissue remodeling has not been well established in the literature. Equally, the role of Citral (inhibitor of retinoid function) in the improvement of lung pathology has not been ascertained in vivo. Therefore, it is hypothesized that ATRA and...
In this paper, an attempt is made to characterise the normal and abnormal breast tissues in infrared images using Riesz and quaternion Hilbert transform based features. Left and right breast regions are separated using midpoint of inframammary folds. Riesz and quaternion based features are extracted from these separated breast tissues. An index bas...
Medical thermography plays a significant role in early detection of breast cancer. The abnormality detection using asymmetry analysis is complex due to low contrast, low signal to noise ratio and absence of clear edges. In this work, asymmetry analysis is carried out on denoised breast thermal images. Block matching and 3D filtering technique (BM3D...