AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Predictive models based on machine learning for bone metastasis in patients with diagnosed colorectal cancer.

Frontiers in public health
BACKGROUND: This study aimed to develop an artificial intelligence predictive model for predicting the probability of developing BM in CRC patients.

Deep learning captures selective features for discrimination of microsatellite instability from pathologic tissue slides of gastric cancer.

International journal of cancer
Microsatellite instability (MSI) status is an important prognostic marker for various cancers. Furthermore, because immune checkpoint inhibitors are much more effective in tumors with high level of MSI (MSI-H), MSI status is routinely tested in multi...

A machine learning model for classifying G-protein-coupled receptors as agonists or antagonists.

BMC bioinformatics
BACKGROUND: G-protein coupled receptors (GPCRs) sense and transmit extracellular signals into the intracellular machinery by regulating G proteins. GPCR malfunctions are associated with a variety of signaling-related diseases, including cancer and di...

Feasibility Study of Constructing a Screening Tool for Adolescent Diabetes Detection Applying Machine Learning Methods.

Sensors (Basel, Switzerland)
Prediabetes and diabetes are becoming alarmingly prevalent among adolescents over the past decade. However, an effective screening tool that can assess diabetes risks smoothly is still in its infancy. In order to contribute to such significant gaps, ...

Graph convolutional network based virus-human protein-protein interaction prediction for novel viruses.

Computational biology and chemistry
Computational identification of human-virus protein-protein interactions (PHIs) is a worthwhile step towards understanding infection mechanisms. Analysis of the PHI networks is important for the determination of pathogenic diseases. Prediction of the...

Deep learning predicts resistance to neoadjuvant chemotherapy for locally advanced gastric cancer: a multicenter study.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Accurate pre-treatment prediction of neoadjuvant chemotherapy (NACT) resistance in patients with locally advanced gastric cancer (LAGC) is essential for timely surgeries and optimized treatments. We aim to evaluate the effectiveness of de...

Prediction algorithm for ICU mortality and length of stay using machine learning.

Scientific reports
Machine learning can predict outcomes and determine variables contributing to precise prediction, and can thus classify patients with different risk factors of outcomes. This study aimed to investigate the predictive accuracy for mortality and length...

An empirical evaluation of sampling methods for the classification of imbalanced data.

PloS one
In numerous classification problems, class distribution is not balanced. For example, positive examples are rare in the fields of disease diagnosis and credit card fraud detection. General machine learning methods are known to be suboptimal for such ...

Assessing the robustness of clinical trials by estimating Jadad's score using artificial intelligence approaches.

Computers in biology and medicine
BACKGROUND: Clinical trials are essential in medical science and are currently the most robust strategy for evaluating the effectiveness of a treatment. However, some of these studies are less reliable than others due to flaws in their design. Assess...

Identification of early invisible acute ischemic stroke in non-contrast computed tomography using two-stage deep-learning model.

Theranostics
Although non-contrast computed tomography (NCCT) is the recommended examination for the suspected acute ischemic stroke (AIS), it cannot detect significant changes in the early infarction. We aimed to develop a deep-learning model to identify early ...