AIMC Topic: Machine Learning

Clear Filters Showing 8281 to 8290 of 34417 articles

Groundwater quality prediction and risk assessment in Kerala, India: A machine-learning approach.

Journal of environmental management
Despite its critical importance for health, agriculture, and the economy, and its key role in supporting climate change adaptation, groundwater quality remains vulnerable to contamination and is often neglected until significant deterioration. The gr...

Abnormal phenotypic defects detection of jujube using explainable machine learning enhanced computer vision.

Journal of food science
Jujube is susceptible to biotic and abiotic adversity stresses resulting in abnormal phenotypic defects. Therefore, abnormal phenotype fruits should be removed during postharvest sorting to increase added value. An improved maximum horizontal diamete...

Prediction model of in-hospital cardiac arrest using machine learning in the early phase of hospitalization.

The Kaohsiung journal of medical sciences
In hospitals, the deterioration of a patient's condition leading to death is often preceded by physiological abnormalities in the hours to days beforehand. Several risk-scoring systems have been developed to identify patients at risk of major adverse...

High Spatiotemporal Precision Mapping of Optical Nanosensor Array Using Machine Learning.

ACS sensors
Optical nanosensors, including single-walled carbon nanotubes (SWCNTs), provide real-time spatiotemporal reporting at the single-molecule level within a nanometer-scale area. However, their superior sensitivity also makes them susceptible to slight e...

Development and validation of a machine learning model to predict myocardial blood flow and clinical outcomes from patients' electrocardiograms.

Cell reports. Medicine
We develop a machine learning (ML) model using electrocardiography (ECG) to predict myocardial blood flow reserve (MFR) and assess its prognostic value for major adverse cardiovascular events (MACEs). Using 3,639 ECG-positron emission tomography (PET...

Deciphering Molecular Embeddings with Centered Kernel Alignment.

Journal of chemical information and modeling
Analyzing machine learning models, especially nonlinear ones, poses significant challenges. In this context, centered kernel alignment (CKA) has emerged as a promising model analysis tool that assesses the similarity between two embeddings. CKA's eff...

Air-Writing Recognition Enabled by a Flexible Dual-Network Hydrogel-Based Sensor and Machine Learning.

ACS applied materials & interfaces
Accurate air-writing recognition is pivotal for advancing state-of-the-art text recognizers, encryption tools, and biometric technologies. However, most existing air-writing recognition systems rely on image-based sensors to track hand and finger mot...

Nutmeg and SPICE: Models and Data for Biomolecular Machine Learning.

Journal of chemical theory and computation
We describe version 2 of the SPICE data set, a collection of quantum chemistry calculations for training machine learning potentials. It expands on the original data set by adding much more sampling of chemical space and more data on noncovalent inte...

Artificial Intelligence Techniques in Grapevine Research: A Comparative Study with an Extensive Review of Datasets, Diseases, and Techniques Evaluation.

Sensors (Basel, Switzerland)
In the last few years, the agricultural field has undergone a digital transformation, incorporating artificial intelligence systems to make good employment of the growing volume of data from various sources and derive value from it. Within artificial...