AIMC Topic: Machine Learning

Clear Filters Showing 1751 to 1760 of 34417 articles

Advancing Aqueous Solubility Prediction: A Machine Learning Approach for Organic Compounds Using a Curated Data Set.

Journal of chemical information and modeling
Aqueous solubility is one key property of a chemical compound that determines its possible use in different applications, from drug development to materials sciences. In this work, we present a model for the prediction of aqueous solubility that leve...

Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm.

Scientific reports
Weeds and crops contribute to a endless resistance for similar assets, which leads to potential declines in crop production and enlarged agricultural expenses. Conventional models of weed control like extensive pesticide use, appear with the hassle o...

Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models.

Scientific reports
The development and refinement of artificial intelligence (AI) and machine learning algorithms have been an area of intense research in radiology and pathology, particularly for automated or computer-aided diagnosis. Whole Slide Imaging (WSI) has eme...

Development and validation of a machine learning model for predicting vulnerable carotid plaques using routine blood biomarkers and derived indicators: insights into sex-related risk patterns.

Cardiovascular diabetology
BACKGROUND: Early detection of vulnerable carotid plaques is critical for stroke prevention. This study aimed to develop a machine learning model based on routine blood tests and derived indices to predict plaque vulnerability and assess sex-specific...

Machine learning pipeline with custom grid search for colorectal Raman spectroscopy data.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Colorectal cancer remains a major health burden, and its early detection is crucial for effective treatment. This study investigates the use of a handheld Raman spectrometer in combination with machine learning to classify colorectal tissue samples c...

Omics-driven strategy develops a tumor biomarker-derived signature to forecast the occurrence and progression of heart failure.

International journal of cardiology
BACKGROUND: Tumor biomarkers have been implicated in heart failure (HF). This study aimed to explore the role of tumor biomarkers in the occurrence and progression of HF.

Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.).

Scientific reports
Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and M...

Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers.

Scientific reports
This study aimed to investigate the potential of peptide mass fingerprints (PMFs) of the serum peptidome using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), in combination with machine learning algorithm...

Exploring the feasibility of AI-based analysis of histopathological variability in salivary gland tumours.

Scientific reports
This study uses artificial intelligence (AI) for differentiation between salivary gland tumours (SGT) using digitised Haematoxylin and Eosin stained whole-slide images (WSI). Machine learning (ML) classifiers were developed and tested using 320 scann...

Maximizing multi-source data integration and minimizing the parameters for greenhouse tomato crop water requirement prediction.

Scientific reports
Accurate scientific predicting of water requirements for protected agriculture crops is essential for informed irrigation management. The Penman-Monteith model, endorsed by the Food and Agriculture Organization of the United Nations (FAO), is current...