Priya Sawant | Savitribai Phule Pune University (original) (raw)

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Papers by Priya Sawant

Journal of Engineering Education Transformations, 2016

Higher educational institutions are encouraged to implement the Outcome-Based Education to prepar... more Higher educational institutions are encouraged to implement the Outcome-Based Education to prepare instructors to be competitive and produce graduates who are ready to meet the global job needs. To determine the level of implementation of the Outcome-Based Education (OBE) in Central Philippines State University, the researcher employed the sequential explanatory mixed-method design which involves two phases: the quantitative followed by qualitative. The quantitative data were collected through a validated survey instrument, while the qualitative data were gathered from the participants through an in-depth semi-structured interview which culled out their experiences on the implementation of the Outcome-Based Education. The findings of the study revealed that Outcome-Based Education standards were moderately implemented in the university. This means that the learning experiences of students and the teaching methodology could hardly develop their skills to attain the intended learning outcomes. Qualitatively, the results yielded different themes that brought forth an eidetic insight that the OBE implementation is collaborative and value-laden effort: bridging theory and practice of the academic community. The research findings were used as a basis for designing the proposed CPSU-Operational Plan using the Approach, Deployment, Learning, Integration (ADLI) model that can be adopted and implemented by the University.

Books by Priya Sawant

Springer , 2022

Computer Aided Diagnostic systems developed to facilitate early detection of pulmonary diseases h... more Computer Aided Diagnostic systems developed to facilitate early detection of pulmonary diseases have exploited texture features to identify radiological patterns on Chest Computed Tomography scans of patients. This paper reviews research studies that have done analysis of texture features to facilitate detection and classification of pulmonary diseases. First, texture and types of texture feature extraction techniques are discussed in brief. Comparison of performance metrics of machine learning-based classifiers used in conjunction with texture feature analysis is also presented. Published research works indicate high performance of second and higher-order statistical feature extraction methods. Support vector machine algorithm exhibits best performance in texture-based disease classification. Finally, we explore the challenges faced in texture analysis and potential future research paths in this domain.

Springer, 2021

In spite of advancements in medical technology, lung diseases continue to cause death and substan... more In spite of advancements in medical technology, lung diseases continue to cause death and substantial morbidity worldwide as these diseases directly affect the respiratory systems and many a times create a layer of lesions on the lungs. A wide gamut of organisms is known to cause various pulmonary infections and newer ones are also emerging. Computer-aided diagnosis (CAD) empowered with image processing and machine learning techniques is an important diagnostic tool for early diagnosis of a disease. These techniques have exhibited a high degree of accuracy. The primary objective of this paper is to present a comprehensive survey of the numerous works carried out to detect lung diseases from CT images using machine learning and deep learning techniques.