Aishwariya Dutta

• Master of Science in Biomedical Engineering
• Lecturer at Military Institution of Science & Technology (MIST)

Recently, numerous studies have been conducted on Missing Value Imputation (MVI), intending the primary solution scheme for the datasets containing one or more missing at�tribute’s values. The incorporation of MVI reinforces the Machine Learning (ML) models’ performance and necessitates a systematic review of MVI methodologies employed for differen...

Background and objective: Automated skin lesion analysis for simultaneous detection and recognition is still challenging for inter-class homogeneity and intra-class heterogeneity, leading to low generic capability of a single convolutional neural network (CNN) with limited datasets. Methods: This article proposes an end-to-end deep CNN-based framew...

Measles is one of the significant public health issues responsible for the high mortality rate around the globe, especially for developing countries. Using nationally representative demographic and health survey data, measles vaccine utilization has been classified, and its underlying factors are identified through an ensemble Machine Learning (ML)...

Acute Lymphoblastic Leukemia (ALL) is a blood cell cancer characterized by the presence of excess immature lymphocytes., Even though automation in ALL prognosis is essential for cancer diagnosis, it remains a challenge due to the morphological correlation between malignant and normal cells. The traditional ALL classification strategy demands that e...

Skin cancer, also known as melanoma, is generally diagnosed visually from the dermoscopic images, which is a tedious and time-consuming task for the dermatologist. Such a visual assessment, via the naked eye for skin cancers, is challenging and arduous due to different artifacts such as low contrast, various noise, presence of hair, fiber, and air...

Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of significant complications, including cardiovascular disease, kidney failure, diabetic retinopathy, and neuropathy, among others, which contribute to an increase in morbidity and mortality rate. If diabetes is diagnosed at an early stage, its severity and u...

Acute Lymphoblastic Leukemia (ALL) is a blood cell cancer characterized by numerous immature lymphocytes. Even though automation in ALL prognosis is an essential aspect of cancer diagnosis, it is challenging due to the morphological correlation between malignant and normal cells. The traditional ALL classification strategy demands experienced patho...

Automated skin lesion analysis for detection and recognition is still challenging for inter-class diversity and intra-class similarity, and the low generic capability of a single Convolutional Neural Network (CNN) with limited datasets. This article proposes an end-to-end deep CNN-based multi-task web application for concurrent detection and recogn...

Skin cancer, also known as melanoma, is generally diagnosed visually from the dermoscopic images, which is a tedious and time-consuming task for the dermatologist. Such a visual assessment, via the naked eye for skin cancers, is a challenging and arduous due to different artifacts such as low contrast, various noise, presence of hair, fiber, and ai...