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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 25 1 Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? Radu-Alexandru Vulpoi; Mihaela Luca; Adrian Ciobanu; Andrei Olteanu; Oana-Bogdana Barboi; Vasile Liviu Drug In: Diagnostics; Volume 12; Issue 4; Pages: 927 (2022) BASE Show details 2 Toward quantitative assessment of deformational plagiocephaly and brachycephaly at the point-of-care Seifabadi, Reza; Aalamifar, Fereshteh; Hezaveh, Seyed Hossein... In: J Med Imaging (Bellingham) (2021) BASE Show details 3 Development of Gaussian Learning Algorithms for Early Detection of Alzheimer's Disease Fang, Chen In: FIU Electronic Theses and Dissertations (2020) Abstract: Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot be reversed or stopped. This research aims to develop Gaussian learning algorithms, natural language processing (NLP) techniques, and mathematical models to effectively delineate the MCI participants from the cognitively normal (CN) group, and identify the most significant brain regions and patterns of changes associated with the progression of AD. The focus will be placed on the earliest manifestations of the disease (early MCI or EMCI) to plan for effective curative/therapeutic interventions and protocols. Multiple modalities of biomarkers have been found to be significantly sensitive in assessing the progression of AD. In this work, several novel multimodal classification frameworks based on proposed Gaussian Learning algorithms are created and applied to neuroimaging data. Classification based on the combination of structural magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers is seen as the most reliable approach for high-accuracy classification. Additionally, changes in linguistic complexity may provide complementary information for the diagnosis and prognosis of AD. For this research endeavor, an NLP-oriented neuropsychological assessment is developed to automatically analyze the distinguishing characteristics of text data in MCI group versus those in CN group. Early findings suggest significant linguistic differences between CN and MCI subjects in terms of word usage, vocabulary, recall, fragmented sentences. In summary, the results obtained indicate a high potential of the neuroimaging-based classification and NLP-oriented assessment to be utilized as a practically computer aided diagnosis system for classification and prediction of AD and its prodromal stages. Future work will ultimately focus on early signs of AD that could help in the planning of curative and therapeutic intervention to slow the progression of the disease. Keyword: Alzheimer’s disease; Biomedical; computer-aided diagnosis; Diagnosis; Diagnostic and Therapeutic Techniques and Equipment; dimensionality reduction; mild cognitive impairment (MCI); multiclass classification; multimodal analysis; Multivariate Analysis; natural language processing (NLP); Other Analytical; Other Biomedical Engineering and Bioengineering; Signal Processing; Statistical Models; Theory and Algorithms URL: https://digitalcommons.fiu.edu/etd/4398 https://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=5672&context=etd BASE Hide details 4 Artificial Intelligence and its future potential in lung cancer screening Joy Mathew, Christopher; David, Ashwini Maria; Joy Mathew, Chris Mariya. - : IfADo - Leibniz Research Centre for Working Environment and Human Factors, Dortmund, 2020 BASE Show details 5 Biomedical applications of voice and speech processing ; Aplicaciones biomédicas del procesamiento de la voz y el habla Gómez Vilda, Pedro In: Loquens; Vol. 4 No. 1 (2017); e035 ; Loquens; Vol. 4 Núm. 1 (2017); e035 ; 2386-2637 ; 10.3989/loquens.2017.v4.i1 (2017) BASE Show details 6 Coronary artery analysis: Computerâ assisted selection of bestâ quality segments in multipleâ phase coronary CT angiography Zhou, Chuan; Chan, Heang‐ping; Hadjiiski, Lubomir M.. - : American Association of Physicists in Medicine, 2016. : Wiley Periodicals, Inc., 2016 BASE Show details 7 A Hybrid Approach to Clinical Question Answering Hasan, Sadid A; Zhu, Xianshu; Dong, Yao... In: DTIC (2014) BASE Show details 8 Computerized analysis of coronary artery disease: Performance evaluation of segmentation and tracking of coronary arteries in CT angiograms Zhou, Chuan; Chan, Heang‐ping; Chughtai, Aamer. - : American Association of Physicists in Medicine, 2014. : Wiley Periodicals, Inc., 2014 BASE Show details 9 Representational and architectural issues in a limited-domain medical speech translator Rayner, Manny; Bouillon, Pierrette; Santaholma, Marianne Elina... In: TALN-RECITAL 2005, Traitement Automatique des Langues Naturelles pp. 163-172 (2005) BASE Show details 10 Eliciting a terminology for mammographic calcifications Alberdi, E; Taylor, P; Lee, R... In: CLIN RADIOL , 57 (11) 1007 - 1013. (2002) (2002) BASE Show details 11 Computer Aided Breast Cancer Diagnosis Floyd, Carey E. In: DTIC AND NTIS (2000) BASE Show details 12 Breast Ultrasound Computer-Aided Diagnosis Approach to Improving Specificity and Decreasing Observer Variability Lo, Joseph In: DTIC AND NTIS (1999) BASE Show details 13 Breast Ultrasound: Computer-Aided Diagnosis Approach to Improving Specificity and Decreasing Observer Variability Baker, Jay A. In: DTIC AND NTIS (1998) BASE Show details 14 Increasing the Accuracy of Mammogram Interpretation Swets, John A. In: DTIC AND NTIS (1998) BASE Show details 15 Computer Aided Breast Cancer Diagnosis. Floyd, Carey E., Jr In: DTIC AND NTIS (1996) BASE Show details 16 Vocal Cord Function and Voice Quality Evaluation of Active Duty U.S. Army Drill Instructors. Mann, Eric A. In: DTIC AND NTIS (1996) BASE Show details 17 Extending the Rule Space Model to a Semantically-Rich Domain: Diagnostic Assessment in Architecture. Katz, Irvin R.; Martinez, Michael E.; Sheehan, Kathleen... In: DTIC AND NTIS (1993) BASE Show details 18 Talking to InterFIS: Adding Speech Input to a Natural Language Interface Everett, Stephanie S.; Wauchope, Kenneth; Perzanowski, Dennis In: DTIC AND NTIS (1992) BASE Show details 19 Computerized Assessment of Individual Differences Hunt, Earl B. In: DTIC AND NTIS (1991) BASE Show details 20 MUMPS Based Integration of Disparate Computer-Assisted Medical Diagnosis Modules Gino, Antonio; Pugh, William M.; Ryman, Dave H.... In: DTIC AND NTIS (1989) BASE Show details Page: 1 2

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