Results 131 to 140 of about 42,332 (292)

PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes

open access: yesAdvanced Science, EarlyView.
A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li   +10 more
wiley   +1 more source

Cardiovascular disease detection from cardiac arrhythmia ECG signals using artificial intelligence models with hyperparameters tuning methodologies

open access: yesHeliyon
Cardiovascular disease (CVD) is connected with irregular cardiac electrical activity, which can be seen in ECG alterations. Due to its convenience and non-invasive aspect, the ECG is routinely exploited to identify different arrhythmias and automatic ECG
Gowri Shankar Manivannan   +3 more
doaj   +1 more source

Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction

open access: yesAdvanced Science, EarlyView.
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen   +3 more
wiley   +1 more source

Optimizing Machine Learning Models for Graduation on Time Prediction: A Comparative Study with Resampling and Hyperparameter Tuning

open access: yesJOIN: Jurnal Online Informatika
Timely graduation prediction is a crucial issue in higher education, especially when academic, demographic, and behavioral factors interact in complex ways.
Rizal Bakri   +3 more
doaj   +1 more source

Artificial Intelligence‐Based Body Composition Analysis Reveals Sex‐Specific Prognostic Markers and Their Clinical Value in Gastric Cancer: A Multicenter Study

open access: yesAdvanced Science, EarlyView.
This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li   +13 more
wiley   +1 more source

ANALISIS PERFORMA CONVOLUTIONAL NEURAL NETWORK DENGAN HYPERPARAMETER TUNING DALAM MENDETEKSI GAMBAR DEEPFAKE

open access: yes
This research analyzes the performance of Convolutional Neural Network (CNN) in detecting deepfake images with a focus on hyperparameter tuning. The study consists of two classes: fake images and real images, with each class containing 5000 data samples.
Darmatasia   +3 more
core   +1 more source

Online Hyperparameter Tuning in Bayesian Optimization for Material Parameter Identification: An Application in Strain-Hardening Plasticity for Automotive Structural Steel

open access: yesAppliedMath
Effective identification of strain-hardening parameters is essential for predictive plasticity models used in automotive applications. However, the performance of Bayesian optimization depends strongly on kernel hyperparameters in the Gaussian-process ...
Teng Long   +3 more
doaj   +1 more source

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

open access: yesAdvanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou   +8 more
wiley   +1 more source

Hyperparameter Tuning Cookbook: A guide for scikit-learn, PyTorch, river, and spotPython

open access: yes, 2023
This document provides a comprehensive guide to hyperparameter tuning using spotPython for scikit-learn, PyTorch, and river. The first part introduces spotPython's surrogate model-based optimization process, while the second part focuses on ...
Bartz-Beielstein, Thomas
core  

Optimizing a Hybrid Deep Learning Model for DDoS Detection Using DBSCAN and PSO

open access: yesJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
This study proposes a hybrid deep learning approach that combines Gated Recurrent Units (GRUs) and Convolutional Neural Networks (CNNs) for Distributed Denial of Service (DDoS) cyberattack detection.
Indrastanti Ratna Widiasari   +1 more
doaj   +1 more source

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