The role of artificial intelligence in early cancer diagnosis
B Hunter, S Hindocha, RW Lee - Cancers, 2022 - mdpi.com
Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …
effective treatment in many tumour groups. Key approaches include screening patients who …
Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review
OT Kee, H Harun, N Mustafa, NA Abdul Murad… - Cardiovascular …, 2023 - Springer
Prediction model has been the focus of studies since the last century in the diagnosis and
prognosis of various diseases. With the advancement in computational technology, machine …
prognosis of various diseases. With the advancement in computational technology, machine …
Methods Used in Computer‐Aided Diagnosis for Breast Cancer Detection Using Mammograms: A Review
SZ Ramadan - Journal of healthcare engineering, 2020 - Wiley Online Library
According to the American Cancer Society's forecasts for 2019, there will be about 268,600
new cases in the United States with invasive breast cancer in women, about 62,930 new …
new cases in the United States with invasive breast cancer in women, about 62,930 new …
Ovarian-adnexal reporting lexicon for MRI: a white paper of the ACR ovarian-adnexal reporting and data systems MRI committee
MRI is used in the evaluation of ovarian and adnexal lesions. MRI can further characterize
lesions seen on ultrasound to help decrease the number of false-positive lesions and avoid …
lesions seen on ultrasound to help decrease the number of false-positive lesions and avoid …
Comparison of logistic regression and artificial neural network models in breast cancer risk estimation
Computer models in medical diagnosis are being developed to help physicians differentiate
between healthy patients and patients with disease. These models can aid in successful …
between healthy patients and patients with disease. These models can aid in successful …
Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibration
BACKGROUND: Discriminating malignant breast lesions from benign ones and accurately
predicting the risk of breast cancer for individual patients are crucial to successful clinical …
predicting the risk of breast cancer for individual patients are crucial to successful clinical …
[HTML][HTML] Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography
Purpose The aim of this study was to compare the performance of image analysis for
predicting breast cancer using two distinct regression models and to evaluate the usefulness …
predicting breast cancer using two distinct regression models and to evaluate the usefulness …
Construction the model on the breast cancer survival analysis use support vector machine, logistic regression and decision tree
CM Chao, YW Yu, BW Cheng, YL Kuo - Journal of medical systems, 2014 - Springer
The aim of the paper is to use data mining technology to establish a classification of breast
cancer survival patterns, and offers a treatment decision-making reference for the survival …
cancer survival patterns, and offers a treatment decision-making reference for the survival …
Optimal breast biopsy decision-making based on mammographic features and demographic factors
Breast cancer is the most common non-skin cancer affecting women in the United States,
where every year more than 20 million mammograms are performed. Breast biopsy is …
where every year more than 20 million mammograms are performed. Breast biopsy is …
When algorithmic predictions use human-generated data: A bias-aware classification algorithm for breast cancer diagnosis
ME Ahsen, MUS Ayvaci… - Information Systems …, 2019 - pubsonline.informs.org
When algorithms use data generated by human beings, they inherit the errors stemming
from human biases, which likely diminishes their performance. We examine the design and …
from human biases, which likely diminishes their performance. We examine the design and …