Taminul Islam, Md. Alif Sheakh, Mst. Sazia Tahosin, Most. Hasna Hena et al.
Breast cancer has rapidly increased in prevalence in recent years, making it one of the leading causes of mortality worldwide. Among all cancers, it is by far the most common. Diagnosing this illness manually requires significant time and expertise. Since detecting breast cancer is a time-consuming ...
Mst. Sazia Tahosin, Md. Alif Sheakh, Taminul Islam, Rishalatun Jannat Lima et al.
Accurately classifying brain tumors using images is extremely important for prognosis and treatment planning. In this study, we have developed an optimized approach using machine learning techniques to classify brain tumors. Our method involves preprocessing the images, extracting features, selectin...
Md. Alif Sheakh, Mst. Sazia Tahosin, Md Maruf Hasan, Taminul Islam et al.
Global attention is now being paid to maternal and child mortality. The incidence of maternal mortality is high in low and middle-income countries, particularly among adolescents and young adults. Healthcare professionals can monitor the mother's heartbeat during pregnancy to determine fetal viabili...
Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Md. Zahid Hasan et al.
Brain tumors are among the most severe health challenges, necessitating early and precise diagnosis for effective treatment planning. This study introduces an optimized hybrid transfer learning (TL) framework for brain tumor classification using magnetic resonance imaging images. The proposed system...
Taminul Islam, Md. Alif Sheakh, Md Rezwane Sadik, Mst. Sazia Tahosin et al.
Social media is an essential component of our personal and professional lives. We use it extensively to share various things, including our opinions on daily topics and feelings about different subjects. This sharing of posts provides insights into someone’s current emotions. In artificial intellige...
Mahadi Hasan, Mst. Sazia Tahosin, Afia Farjana, Md. Alif Sheakh et al.
Anemia is a major issue for public health with significant implications for national development, it remains a largely neglected health problem in many developing countries. Iron deficiency is responsible for at least 50% of all cases of anemia and kills nearly 1 million people each year. Africa and...
Md. Alif Sheakh, Sami Azam, Mst. Sazia Tahosin, Asif Karim et al.
• ECgMLP offers a novel approach for automated diagnosis of endometrial cancer. • Advanced preprocessing boosts histopathological image quality and accuracy. • Otsu thresholding and watershed aid in precise image segmentation. • ECgMLP achieves 99.26 % accuracy, surpassing prior diagnostic technique...
Utsha Roy, Mst. Sazia Tahosin, Md. Mahedi Hassan, Taminul Islam et al.
The rise of fake news has made the need for effective detection methods, including in languages other than English, increasingly important. The study aims to address the challenges of Bangla which is considered a less important language. To this end, a complete dataset containing about 50,000 news i...
Md. Alif Sheakh, Mst. Sazia Tahosin, Mohammad Jahangir Alam, Mahbuba Begum
Sadia Sultana Chowa, Md. Rahad Islam Bhuiyan, Mst. Sazia Tahosin, Asif Karim et al.
This study presents a novel privacy-preserving self-supervised (SSL) framework for COVID-19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier homomorphic encryption (PHE) to prevent third-party attacks during training. The FL-SSL based framework employs two ...
Tasnim Bill Zannah, Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin et al.
Fetal health monitoring is vital for early diagnosis and intervention during pregnancy, with cardiotocography (CTG) being a standard tool for assessing fetal well-being. However, CTG interpretation often suffers from subjectivity and inconsistency, motivating the need for automated, accurate, and in...
Isha Das, Md. Alif Sheakh, Shahab Abdulla, Mst. Sazia Tahosin et al.
X-ray imaging remains a cornerstone in medical diagnostics for conditions such as bone fractures, knee osteoarthritis, and lung diseases. However, variability in image quality and dataset diversity presents significant challenges for automated analysis using deep learning models. This study addresse...
Mst. Sazia Tahosin, Md. Alif Sheakh, Mohammad Jahangir Alam, Md. Mehedi Hassan et al.
Advances in deep learning have transformed medical imaging, yet progress is hindered by data privacy regulations and fragmented datasets across institutions. To address these challenges, we propose FedVGM, a privacy-preserving federated learning framework for multi-modal medical image analysis. FedV...
Md. Nazmus Sakib, Md. Alif Sheakh, Mst. Sazia Tahosin, Md Rezwane Sadik et al.
Thyroid disease is a medical condition that prevents a person's thyroid gland from producing enough hormones and significantly affects a person's health. Early detection of thyroid disease and timely treatment can play an essential role in improving the health of thyroid patients. Our research paper...
Md. Alif Sheakh, Mst. Sazia Tahosin, Lima Akter, Israt Jahan et al.
This study aims to identify the most accurate machine learning algorithm for predicting heart attacks using demographic data, physiological measurements, and electrocardiogram (ECG) results. We utilized a dataset of 4,000 patient records, combining data from DMCH and Kaggle. Our methodology involved...