Artificial Intelligence Medical Compendium

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

Showing 61 to 70 of 6,466 articles

Classifying social and physical pain from multimodal physiological signals using machine learning.

Scientific reports
Accurate pain assessment is essential for effective management; however, most studies have focused on differentiating pain from non-pain or estimating pain intensity rather than distinguishing between distinct pain types. We present a machine learnin... read more 

Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.

Scientific reports
The Ki67 score is a crucial prognostic biomarker for neuroendocrine tumors, but its manual assessment is labor-intensive, requiring the counting of 500-2,000 cells in hotspots. Digital image analysis could streamline this process, yet few comprehensi... read more 

Supervised learning of the Jaynes-Cummings Hamiltonian.

Scientific reports
We investigate the utility of deep neural networks (DNNs) in estimating the Jaynes-Cummings Hamiltonian's parameters from its energy spectrum alone. We assume that the energy spectrum may or may not be corrupted by noise. In the noiseless case, we us... read more 

A hybrid filtering and deep learning approach for early Alzheimer's disease identification.

Scientific reports
Alzheimer's disease is a progressive neurological disorder that profoundly affects cognitive functions and daily activities. Rapid and precise identification is essential for effective intervention and improved patient outcomes. This research introdu... read more 

A convolutional neural network-based deep learning approach for predicting surface chloride concentration of concrete in marine tidal zones.

Scientific reports
Chloride-induced corrosion is a major threat to the durability of reinforced concrete (RC) structures. This is especially critical in marine tidal zones, where surface chloride concentration (Cs) plays a key role in predicting chloride ingress using ... read more 

Dentists' perception and use of AI and robotics in the care of persons with disabilities.

Scientific reports
Despite the growing role of AI and robotics in healthcare, little is known about their integration into dental care for persons with disabilities (PWDs) in Saudi Arabia. This study aimed to assess dentists' perceptions and attitudes towards and use o... read more 

Prediction of MGMT methylation status in glioblastoma patients based on radiomics feature extracted from intratumoral and peritumoral MRI imaging.

Scientific reports
Assessing MGMT promoter methylation is crucial for determining appropriate glioblastoma therapy. Previous studies have focused on intratumoral regions, overlooking the peritumoral area. This study aimed to develop a radiomic model using MRI-derived f... read more 

Evaluating the efficacy of using large language models in preoperative prediction of microvascular invasion in HCC: a multicenter study.

Scientific reports
Primary liver cancer is the sixth most commonly diagnosed cancer globally and the third leading cause of cancer-related deaths. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and microvascular invasion (MVI) is a sign... read more 

Integration of Google Earth Engine, Sentinel-2 images, and machine learning for temporal mapping of total dissolved solids in river systems.

Scientific reports
One of the important indicators of water quality (WQ) in inland water systems is total dissolved solids (TDS). Collecting and maintaining in situ TDS data with high spatial and temporal resolution is time and money-consuming. This study highlights an... read more 

Deep learning-based automatic diagnosis of rice leaf diseases using ensemble CNN models.

Scientific reports
Rice diseases pose a critical threat to global crop yields, underscoring the need for rapid and accurate diagnostic tools to ensure effective crop management and productivity. Traditional diagnostic approaches often lack both precision and scalabilit... read more