AIMC Topic: Algorithms

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Intrinsic growth rate and evolution of the Premnotrypes Vorax population using fuzzy information.

Bio Systems
The white potato worm (Premnotrypes Vorax (Hustache)) is one of the pests that causes the greatest damage to the potato crop and the greatest economic losses to the grower; therefore, knowing its life cycle and estimating its intrinsic growth rate is...

Prediction of monthly evapotranspiration by artificial neural network model development with Levenberg-Marquardt method in Elazig, Turkey.

Environmental science and pollution research international
The phenomenon of evapotranspiration (ET) is closely linked to the issue of water scarcity, as it involves water loss through both evaporation and plant transpiration. Accurate prediction of evapotranspiration is of utmost importance in the strategic...

A journey from omics to clinicomics in solid cancers: Success stories and challenges.

Advances in protein chemistry and structural biology
The word 'cancer' encompasses a heterogenous group of distinct disease types characterized by a spectrum of pathological features, genetic alterations and response to therapies. According to the World Health Organization, cancer is the second leading...

Improved QSAR models for PARP-1 inhibition using data balancing, interpretable machine learning, and matched molecular pair analysis.

Molecular diversity
The poly (ADP-ribose) polymerase-1 (PARP-1) enzyme is an important target in the treatment of breast cancer. Currently, treatment options include the drugs Olaparib, Niraparib, Rucaparib, and Talazoparib; however, these drugs can cause severe side ef...

Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction.

Magnetic resonance in medicine
PURPOSE: To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP).

Tooth numbering and classification on bitewing radiographs: an artificial intelligence pilot study.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: The aim of this study is to assess the efficacy of employing a deep learning methodology for the automated identification and enumeration of permanent teeth in bitewing radiographs. The experimental procedures and techniques employed in th...

INTERPRETABLE MACHINE LEARNING FOR PREDICTING RISK OF INVASIVE FUNGAL INFECTION IN CRITICALLY ILL PATIENTS IN THE INTENSIVE CARE UNIT: A RETROSPECTIVE COHORT STUDY BASED ON MIMIC-IV DATABASE.

Shock (Augusta, Ga.)
The delayed diagnosis of invasive fungal infection (IFI) is highly correlated with poor prognosis in patients. Early identification of high-risk patients with invasive fungal infections and timely implementation of targeted measures is beneficial for...

Upper gastrointestinal haemorrhage patients' survival: A causal inference and prediction study.

European journal of clinical investigation
BACKGROUND: Upper gastrointestinal (GI) bleeding is a common medical emergency. This study aimed to develop models to predict critically ill patients with upper GI bleeding in-hospital and 30-day survival, identify the correlation factor and infer th...

A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals.

Medical & biological engineering & computing
In recent years, fatigue driving has become the main cause of traffic accidents, leading to increased attention towards fatigue detection systems. However, the pooling and strided convolutional operations in fatigue detection algorithm based on tradi...

Delay-dependent Lurie-Postnikov type Lyapunov-Krasovskii functionals for stability analysis of discrete-time delayed neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper addresses the influence of time-varying delay and nonlinear activation functions with sector restrictions on the stability of discrete-time neural networks. Compared to previous works that mainly focuses on the influence of delay informati...