Extracting cancer concepts from clinical notes using natural language processing: a systematic review
M Gholipour, R Khajouei, P Amiri… - BMC …, 2023 - Springer
Background Extracting information from free texts using natural language processing (NLP)
can save time and reduce the hassle of manually extracting large quantities of data from …
can save time and reduce the hassle of manually extracting large quantities of data from …
Classification and diagnostic prediction of breast cancer metastasis on clinical data using machine learning algorithms
M Botlagunta, MD Botlagunta, MB Myneni… - Scientific Reports, 2023 - nature.com
Abstract Metastatic Breast Cancer (MBC) is one of the primary causes of cancer-related
deaths in women. Despite several limitations, histopathological information about the …
deaths in women. Despite several limitations, histopathological information about the …
[HTML][HTML] The stratified K-folds cross-validation and class-balancing methods with high-performance ensemble classifiers for breast cancer classification
Breast cancer is one of the most common causes of death among women, and early
diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used …
diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used …
Heart disease prediction using distinct artificial intelligence techniques: performance analysis and comparison
Consolidated efforts have been made to enhance the treatment and diagnosis of heart
disease due to its detrimental effects on society. As technology and medical diagnostics …
disease due to its detrimental effects on society. As technology and medical diagnostics …
An effective approach for early liver disease prediction and sensitivity analysis
The liver is one of the most vital organs of the human body. Even when partially injured, it
functions normally. Therefore, detecting liver diseases at the early stages is challenging …
functions normally. Therefore, detecting liver diseases at the early stages is challenging …
Enhancing breast cancer detection and classification using advanced multi-model features and ensemble machine learning techniques
Breast cancer (BC) is the most common cancer among women, making it essential to have
an accurate and dependable system for diagnosing benign or malignant tumors. It is …
an accurate and dependable system for diagnosing benign or malignant tumors. It is …
An explainable artificial intelligence model for the classification of breast cancer
Breast cancer is the most common cancer among women and globally affects both genders.
The disease arises due to abnormal growth of tissue formed of malignant cells. Early …
The disease arises due to abnormal growth of tissue formed of malignant cells. Early …
Constructing perturbation matrices of prototypes for enhancing the performance of fuzzy decoding mechanism
Granular computing (GrC) embraces a spectrum of concepts, methodologies, methods, and
applications, which dwells upon information granules and their processing. Fuzzy C‐means …
applications, which dwells upon information granules and their processing. Fuzzy C‐means …
Hybrid salp swarm and grey wolf optimizer algorithm based ensemble approach for breast cancer diagnosis
K Rustagi, P Bhatnagar, R Mathur, I Singh - Multimedia Tools and …, 2024 - Springer
In the world, cancer is listed as the second leading cause of death. Breast cancer is one of
the types that affects women more often than men, and because it has a high mortality rate …
the types that affects women more often than men, and because it has a high mortality rate …
Prediction of breast cancer based on computer vision and artificial intelligence techniques
Breast cancer is a leading cause of mortality among women. Early detection will increase
the chances of successful treatment and minimize the death rate. Even though many studies …
the chances of successful treatment and minimize the death rate. Even though many studies …