AIMC Topic: Machine Learning

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Artificial Intelligence-Based Ensemble Learning Model for Prediction of Hepatitis C Disease.

Frontiers in public health
Machine learning algorithms are excellent techniques to develop prediction models to enhance response and efficiency in the health sector. It is the greatest approach to avoid the spread of hepatitis C, especially injecting drugs, is to avoid these b...

Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method.

Computational intelligence and neuroscience
White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the immune system. They are also known as "defender cells." But the imbalance in the number of WBCs in the blood can be hazardous. Leukemia is the most common bl...

Transferability of features for neural networks links to adversarial attacks and defences.

PloS one
The reason for the existence of adversarial samples is still barely understood. Here, we explore the transferability of learned features to Out-of-Distribution (OoD) classes. We do this by assessing neural networks' capability to encode the existing ...

Federated Learning in Medical Imaging: Part I: Toward Multicentral Health Care Ecosystems.

Journal of the American College of Radiology : JACR
With recent developments in medical imaging facilities, extensive medical imaging data are produced every day. This increasing amount of data provides an opportunity for researchers to develop data-driven methods and deliver better health care. Howev...

Predicting Actions of Users Using Heterogeneous Online Signals.

Big data
Advertising platforms have a growing need for improving prediction quality, as missing out on ad opportunities can have a negative effect on their performance. To that end, prediction tasks such as conversion prediction need to be continuously advanc...

Applications of natural language processing in radiology: A systematic review.

International journal of medical informatics
BACKGROUND: Recent advances in performance of natural language processing (NLP) techniques have spurred wider use and more sophisticated applications of NLP in radiology. This study systematically reviews the trends and applications of NLP in radiolo...

Predicting exclusive breastfeeding in maternity wards using machine learning techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Adequate support in maternity wards is decisive for breastfeeding outcomes during the first year of life. Quality improvement interventions require the identification of the factors influencing hospital benchmark indicators....

DACFL: Dynamic Average Consensus-Based Federated Learning in Decentralized Sensors Network.

Sensors (Basel, Switzerland)
Federated Learning (FL) is a privacy-preserving way to utilize the sensitive data generated by smart sensors of user devices, where a central parameter server (PS) coordinates multiple user devices to train a global model. However, relying on central...

A novel liver cancer diagnosis method based on patient similarity network and DenseGCN.

Scientific reports
Liver cancer is the main malignancy in terms of mortality rate, accurate diagnosis can help the treatment outcome of liver cancer. Patient similarity network is an important information which helps in cancer diagnosis. However, recent works rarely ta...

Toward the explainability, transparency, and universality of machine learning for behavioral classification in neuroscience.

Current opinion in neurobiology
The use of rigorous ethological observation via machine learning techniques to understand brain function (computational neuroethology) is a rapidly growing approach that is poised to significantly change how behavioral neuroscience is commonly perfor...