AIMC Topic: Neural Networks, Computer

Clear Filters Showing 7451 to 7460 of 31376 articles

Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.

Current problems in cancer
Skin cancer, including the highly lethal malignant melanoma, poses a significant global health challenge with a rising incidence rate. Early detection plays a pivotal role in improving survival rates. This study aims to develop an advanced deep learn...

Fusion-based approach for hydrometeorological drought modeling: a regional investigation for Iran.

Environmental science and pollution research international
The objective of this study was to model a new drought index called the Fusion-based Hydrological Meteorological Drought Index (FHMDI) to simultaneously monitor hydrological and meteorological drought. Aiming to estimate drought more accurately, loca...

Evaluation metrics and statistical tests for machine learning.

Scientific reports
Research on different machine learning (ML) has become incredibly popular during the past few decades. However, for some researchers not familiar with statistics, it might be difficult to understand how to evaluate the performance of ML models and co...

Bayesian inference is facilitated by modular neural networks with different time scales.

PLoS computational biology
Various animals, including humans, have been suggested to perform Bayesian inferences to handle noisy, time-varying external information. In performing Bayesian inference by the brain, the prior distribution must be acquired and represented by sampli...

End-to-end deep learning approach to mouse behavior classification from cortex-wide calcium imaging.

PLoS computational biology
Deep learning is a powerful tool for neural decoding, broadly applied to systems neuroscience and clinical studies. Interpretable and transparent models that can explain neural decoding for intended behaviors are crucial to identifying essential feat...

Predictive value of ultrasonic artificial intelligence in placental characteristics of early pregnancy for gestational diabetes mellitus.

Frontiers in endocrinology
BACKGROUND: To explore the predictive value of placental features in early pregnancy for gestational diabetes mellitus (GDM) using deep and radiomics-based machine learning (ML) applied to ultrasound imaging (USI), and to develop a nomogram in conjun...

Application of artificial neural networks to evaluate femur development in the human fetus.

PloS one
The present article concentrates on an innovative analysis that was performed to assess the development of the femur in human fetuses using artificial intelligence. As a prerequisite, linear dimensions, cross-sectional surface areas and volumes of th...

Detection and coverage estimation of purple nutsedge in turf with image classification neural networks.

Pest management science
BACKGROUND: Accurate detection of weeds and estimation of their coverage is crucial for implementing precision herbicide applications. Deep learning (DL) techniques are typically used for weed detection and coverage estimation by analyzing informatio...

Deepm6A-MT: A deep learning-based method for identifying RNA N6-methyladenosine sites in multiple tissues.

Methods (San Diego, Calif.)
N6-methyladenosine (m6A) is the most prevalent, abundant, and conserved internal modification in the eukaryotic messenger RNA (mRNAs) and plays a crucial role in the cellular process. Although more than ten methods were developed for m6A detection ov...

Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods.

Computer methods and programs in biomedicine
BACKGROUND: Estimating the risk of a difficult tracheal intubation should help clinicians in better anaesthesia planning, to maximize patient safety. Routine bedside screenings suffer from low sensitivity.