AI Medical Compendium Journal:
PeerJ

Showing 51 to 60 of 90 articles

: a novel hybrid quasi-fuzzy artificial neural network (ANN) model for estimation of reference evapotranspiration.

PeerJ
Reference evapotranspiration ( ) is a significant parameter for efficient irrigation scheduling and groundwater conservation. Different machine learning models have been designed for estimation for specific combinations of available meteorological p...

Improving plant miRNA-target prediction with self-supervised k-mer embedding and spectral graph convolutional neural network.

PeerJ
Deciphering the targets of microRNAs (miRNAs) in plants is crucial for comprehending their function and the variation in phenotype that they cause. As the highly cell-specific nature of miRNA regulation, recent computational approaches usually utiliz...

Machine learning approaches to debris flow susceptibility analyses in the Yunnan section of the Nujiang River Basin.

PeerJ
BACKGROUND: The Yunnan section of the Nujiang River (YNR) Basin in the alpine-valley area is one of the most critical areas of debris flow in China.

A retrospective prognostic evaluation using unsupervised learning in the treatment of COVID-19 patients with hypertension treated with ACEI/ARB drugs.

PeerJ
INTRODUCTION: This study aimed to evaluate the prognosis of patients with COVID-19 and hypertension who were treated with angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor B (ARB) drugs and to identify key features affecting patient...

Global marine phytoplankton dynamics analysis with machine learning and reanalyzed remote sensing.

PeerJ
Phytoplankton are the world's largest oxygen producers found in oceans, seas and large water bodies, which play crucial roles in the marine food chain. Unbalanced biogeochemical features like salinity, pH, minerals, ., can retard their growth. With a...

An adaptive data-driven architecture for mental health care applications.

PeerJ
BACKGROUND: In the current era of rapid technological innovation, our lives are becoming more closely intertwined with digital systems. Consequently, every human action generates a valuable repository of digital data. In this context, data-driven arc...

Predicting central cervical lymph node metastasis in papillary thyroid microcarcinoma using deep learning.

PeerJ
BACKGROUND: The aim of this study is to design a deep learning (DL) model to preoperatively predict the occurrence of central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC).

High-resolution density assessment assisted by deep learning of (Lamarck, 1816) and (Linnaeus, 1767) in rocky circalittoral shelf of Bay of Biscay.

PeerJ
This study presents a novel approach to high-resolution density distribution mapping of two key species of the 1170 "Reefs" habitat, and , in the Bay of Biscay using deep learning models. The main objective of this study was to establish a pipeline ...

Tracking mosquito-borne diseases via social media: a machine learning approach to topic modelling and sentiment analysis.

PeerJ
Mosquito-borne diseases (MBDs) are a major threat worldwide, and public consultation on these diseases is critical to disease control decision-making. However, traditional public surveys are time-consuming and labor-intensive and do not allow for tim...

Wood identification based on macroscopic images using deep and transfer learning approaches.

PeerJ
Identifying forest types is vital for evaluating the ecological, economic, and social benefits provided by forests, and for protecting, managing, and sustaining them. Although traditionally based on expert observation, recent developments have increa...