While ML models are powerful tools for predicting diabetes, their lack of interpretability presents a major challenge for clinical adoption. Healthcare professionals require AI models to not only be ...

To develop a machine learning (ML) algorithm to predict survival probabilities for patients with epithelial ovarian cancer (EOC).Data were obtained from the SEER database for women diagnosed with EOC ...

By Tarun Sai Lomte COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological ...

Deep learning models go above and beyond traditional machine learning and can process data and recognize patterns much more efficiently.

At first glance, machine learning might seem mysterious, but it’s built on a logical foundation. Let’s explore how each step works to make sense of the data: ...

Should you grab your umbrella before you walk out the door? Checking the weather forecast beforehand will only be helpful if that forecast is accurate.

After combing through 4,000 existing medications, an artificial intelligence tool helped uncover one that saved the life of a ...

Brain metastases, the most common type of brain ... datasets and refine the AI model for clinical use. More information: Keyhan Najafian et al, Machine learning prediction of brain metastasis ...

One of the promising applications of machine learning is in precision medicine, where disease risk is predicted using patient genetic data. However, creating an accurate prediction model based on ...