000			02022nam a22003257a 4500
003			OSt
005			20250714181601.0
008			250714b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH QA 76 _bH57 2025
100			_aHipulan, John Gerald M. _eauthor
245			_aProhealth suite: _bPtb portal with yolo11 capabilities/ _cJohn Gerald M. Hipulan, Davis Louis A. Icaro, Kyle Gabriel Kristofferson S. Maraya, Aaron Paul M. Sicio, and Paolo Miguel L. Sunga.--
260			_aManila: _bTechnological University of the Philippines, _c2025.
300			_aix, 77pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Science.-- _bBachelor of science in computer science: _cTechnological University of the Philippines, _d2025.
504			_aIncludes bibliographic references and index.
520			_aEarly detection and diagnosis of diseases are critical to improving patient outcomes and reducing mortality rates. This thesis presents the ProHealth Suite, a diagnostic tool that leverages YOLOv11 to detect pleural effusion and cavities—conditions that may indicate probable pulmonary tuberculosis—from medical images, using chest X-rays as the primary input. This research demonstrates the potential of YOLOv11 in automating and improving the accuracy of disease detection, potentially enhancing the early diagnosis process in clinical settings. The ProHealth Suite represents a significant step towards the development of comprehensive, AI-powered diagnostic tools that can be widely implemented in healthcare systems worldwide.
650			_aSmart diagnostics
650			_aAI-powered TB detection
650			_aReal-time health screening
700			_aIcaro, Davis Louis A. _eauthor
700			_aMaraya, Kyle Gabriel Kristofferson S. _eauthor
700			_aSicio, Aaron Paul M. _eauthor
700			_aSunga, Paolo Miguel L. _eauthor
942			_2lcc _cBTH COS _n0
999			_c30326 _d30326