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<title>DEPARTMENT  OF  MANAGEMENT INFORMATION SYSTEM</title>
<link href="http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14010" rel="alternate"/>
<subtitle/>
<id>http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14010</id>
<updated>2026-04-05T17:30:11Z</updated>
<dc:date>2026-04-05T17:30:11Z</dc:date>
<entry>
<title>Analyzing The Challenges Of Management Information System Implementation: A Case Study Of Healthcare Sector In Bangladesh</title>
<link href="http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14271" rel="alternate"/>
<author>
<name>Sakim, Md Abdus</name>
</author>
<id>http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14271</id>
<updated>2025-09-03T21:01:52Z</updated>
<published>2024-02-03T00:00:00Z</published>
<summary type="text">Analyzing The Challenges Of Management Information System Implementation: A Case Study Of Healthcare Sector In Bangladesh
Sakim, Md Abdus
In the rapidly changing world of technology, this study delves into the complexities and challenges faced in the implementation of Management Information Systems (MIS) in the healthcare sector of Bangladesh. Recognizing the crucial role of technology in enhancing healthcare delivery, this research aims to provide an in-depth understanding of the specific barriers and difficulties encountered in the adoption and effective use of MIS in this vital sector. Through a comprehensive case study approach, the study meticulously examines various factors, including technological, human resource, financial, cultural, and policy-related challenges. It also considers the perspectives of multiple stakeholders, such as healthcare providers, managers, and IT professionals, to provide a holistic view of the MIS implementation landscape. The importance of this research lies in its dual contribution to both academic understanding and practical application. Academically, it enriches the discourse on MIS implementation in developing countries, particularly within the healthcare sector, by offering empirical evidence and in-depth analysis from the context of Bangladesh. Practically, it serves as a valuable guide for healthcare professionals, policymakers, and technology specialists, offering strategic insights and recommendations tailored to overcome the identified challenges.
Thesis
</summary>
<dc:date>2024-02-03T00:00:00Z</dc:date>
</entry>
<entry>
<title>The Impact of Depression and Stress on Preterm Births in First-Time Mothers:</title>
<link href="http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14270" rel="alternate"/>
<author>
<name/>
</author>
<id>http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14270</id>
<updated>2025-09-03T21:01:46Z</updated>
<published>2024-02-03T00:00:00Z</published>
<summary type="text">The Impact of Depression and Stress on Preterm Births in First-Time Mothers:
This thesis looks at the relationship between stress, depression, and preterm births among first-time mothers in Bangladesh. Preterm births are defined as births that happen before 37 weeks of gestation, and they have a lot of health implications for both the mother and the baby. Stress and depression have been identified as potential risk factors for preterm births, but it is unclear how specifically they affect this issue in Bangladesh. The increased number of preterm births has raised concerns in recent years since it presents serious risks to the health of both the mother and the newborn. Preterm birth mechanisms continue to be complicated and multifactorial, despite international efforts to address this issue. The specific experiences of first-time mothers in Bangladesh are the main focus of this study, which also acknowledges the possible interactions between healthcare, cultural, and economic factors that may make this demographic more vulnerable to mental health issues during pregnancy. A mixed-methods strategy is used in the inquiry to collect thorough data, which combines quantitative surveys and qualitative interviews. First-time pregnant women's stress and depression levels are measured using standardized instruments as part of the quantitative component. Qualitative interviews, on the other hand, offer a more profound comprehension of the environmental and cultural elements that either exacerbate or lessen the effects of stress and depression on premature births. The results of this study may influence public health policy and focused interventions meant to enhance maternal mental health in Bangladesh. This study adds significant insights to the global conversation on maternal healthcare by highlighting the links between depression, stress, and preterm births in first-time mothers. It also highlights the importance of culturally appropriate methods for addressing mental health issues during pregnancy. In the end, the findings of this research might open the door to more practical approaches to lessen the incidence of preterm deliveries and enhance the general health of mothers and children in Bangladesh and other comparable settings
Project
</summary>
<dc:date>2024-02-03T00:00:00Z</dc:date>
</entry>
<entry>
<title>A Machine Learning Approach for Early Detection and Improved Decision-Making for Lung Cancer Diagnosis</title>
<link href="http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14269" rel="alternate"/>
<author>
<name>Hasan, Km. Zayedul</name>
</author>
<id>http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14269</id>
<updated>2025-09-03T21:01:51Z</updated>
<published>2024-02-03T00:00:00Z</published>
<summary type="text">A Machine Learning Approach for Early Detection and Improved Decision-Making for Lung Cancer Diagnosis
Hasan, Km. Zayedul
Lung cancer is presently the leading cause of cancer-related mortalities worldwide. Environmental conditions, lifestyle habits, and genetics are the main causes of lung cancer. Early detection of lung cancer is pivotal in preventing its severe consequences. The integration of machine learning algorithms in the healthcare industry has led to significant advancements in disease diagnosis. These algorithms help medical professionals diagnose lung cancer accurately in the early stages. In this study, we propose using Quadratic Discriminant Analysis to improve the accuracy of lung cancer diagnosis by analyzing the symptoms of lung cancer patients. Our proposed technique is more suitable for diagnosing lung cancer with higher accuracy and precision compared to previous techniques. The methodology has demonstrated an impressive overall accuracy of 98% based on empirical results.
Thesis
</summary>
<dc:date>2024-02-03T00:00:00Z</dc:date>
</entry>
<entry>
<title>Navigating the Skills Landscape: A Comprehensive Analysis of the Job Industry in Bangladesh</title>
<link href="http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14268" rel="alternate"/>
<author>
<name>zaman, Md. Hasanuz</name>
</author>
<id>http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14268</id>
<updated>2025-09-03T21:01:42Z</updated>
<published>2024-02-03T00:00:00Z</published>
<summary type="text">Navigating the Skills Landscape: A Comprehensive Analysis of the Job Industry in Bangladesh
zaman, Md. Hasanuz
This thesis explores the complexities of Bangladesh's employment market, considering the global workforce changes. It uses a multifaceted methodology, incorporating quantitative and qualitative approaches, to understand the dynamic interactions between skill demands, industry changes, and employers' needs. The study also examines the alignment between academic qualifications and industry requirements, addressing difficulties faced by job seekers and providing guidance for educational institutions. The research also projects future trends and offers a forward-looking perspective, assisting professionals, educators, and policymakers in navigating Bangladesh's complex skills ecosystem. The thesis contributes to ongoing discussions on employability, skill development and the strategic alignment of education with industry demands.
Thesis
</summary>
<dc:date>2024-02-03T00:00:00Z</dc:date>
</entry>
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