Design And Development Of Machine Learning Based Classification And Detection System For Brain Hemorrhage Disease
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Abstract
Brain hemorrhage is a critical medical condition characterized by bleeding within the brain
newlinetissue. This bleeding can lead to severe neurological deficits, increasing the risk of permanent
newlinedamage or death if not promptly addressed. The assessment of brain hemorrhage involves
newlineevaluating the extent of bleeding and its impact on surrounding brain structures. Timely
newlineevaluation is crucial to initiate appropriate medical interventions and minimize further
newlineneurological damage. Morphological and volumetric assessments play a vital role in
newlinediagnosing brain hemorrhage, including parameters such as hematoma size, mass effect on
newlineadjacent structures, and volume of displaced brain tissue. Early diagnosis enables prompt
newlinemedical management to mitigate complications and optimize patient outcomes.
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