Abstract: Deep learning-based models have revolutionized medical diagnostics by using Big Data to enhance disease diagnosis and clinical decision-making. However, their significant computational ...

Abstract: The current variants of the Segment Anything Model (SAM), which include the original SAM and Medical SAM, still lack the capability to produce sufficiently accurate segmentation for medical ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

ABSTRACT: Malaria remains a major public health challenge in the Democratic Republic of Congo (DRC), particularly in Lubumbashi, where traditional diagnostic methods are struggling to meet growing ...

Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...

Machine-learning models identify relationships in a data set (called the training data set) and use this training to perform operations on data that the model has not encountered before. This could ...

Artificial intelligence startup OpenEvidence says its AI model has scored a perfect 100% on the United States Medical Licensing Examination (USMLE), raising the bar on the proficiency of AI models to ...

Steal a Brainrot Fuse Machine lets players combine up to four Brainrots for new, rare ones. There are two new secret Brainrots and several fusion combos with unique odds. Players can speed up fusions ...

You will be redirected to our submission process. The “Machine Learning for Medical Image Analysis” Research Topic is dedicated to presentations from the 29th Conference in Medical Image Understanding ...

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Integrating intelligent technologies like artificial intelligence (AI) and machine learning (ML) into supply chain management can enhance predictive maintenance, improve quality control, and detect ...