Optimal image settings for object detection of Iba1 immunolabelled cells in DAB. by Danish M. Anwer (15383441)

Timeline of the decision-making process regarding antimicrobial therapy in ICU. by Davide Ferrari (163517)

Rapid Prediction of Chemical Ecotoxicity Through Genetic Algorithm Optimized Neural Network Models by Ping Hou (17213)

“…To reduce the manual tuning effort on optimal network architecture, a genetic algorithm is investigated to automatically search and configure the network architecture. …”

Supporting data for “Digital immunochromatography: A bead-based bilateral zigzag flow immuno-assay with adaptive differential noise correction for rapid and precise protein detecti... by Zhiting Peng (9722516)

Seamless integration of legacy robotic systems into a self-driving laboratory via NIMO: a case study on liquid handler automation by Ryo Tamura (1957942)

“…As a proof of concept, we integrated an automated liquid handling system controlled by a Visual Basic (VB) program into the SDL through NIMO and performed parameter optimization of the dispensing process using Bayesian optimization, thereby enabling autonomous and automated experiments. …”

A schematic view of the step-by-step computational approach in the current study. by Hamed Rezaei (11085366)

Overview of PREDICATE developed to create viral biomass reactions and predict host-based antiviral targets using host-virus models. by Nantia Leonidou (14833068)

Workflow overview to reconstruct integrated host-virus genome-scale models and detect promising compounds with an antiviral activity. by Nantia Leonidou (14833068)

Schematic overview of the XBSI framework. by Rajeev Bopche (20208606)

Human-Guided Metaverse Synthesis for Quantum Dots: Advancing Nanomaterial Research through Augmented Artificial Intelligence by Yao Xu (247302)

“…This study proposes an innovative paradigm for metaverse-based synthesis experiments, aiming to enhance experimental optimization efficiency through human-guided parameter tuning in the metaverse and augmented artificial intelligence (AI) with human expertise. …”

Human-Guided Metaverse Synthesis for Quantum Dots: Advancing Nanomaterial Research through Augmented Artificial Intelligence by Yao Xu (247302)

“…This study proposes an innovative paradigm for metaverse-based synthesis experiments, aiming to enhance experimental optimization efficiency through human-guided parameter tuning in the metaverse and augmented artificial intelligence (AI) with human expertise. …”

Data_Sheet_1_Automated risk assessment of newly detected atrial fibrillation poststroke from electronic health record data using machine learning and natural language processing.PD... by Sheng-Feng Sung (616343)

Video-to-Model Data Set by Sönke Knoch (8616117)

“…</div><div><br></div><div>Abstract: Manual activities are often hidden deep down in discrete manufacturing processes. For the elicitation and optimization of process behavior, complete information about the execution of Manual activities are required. …”

Data_Sheet_1_Early Prediction of Cardiogenic Shock Using Machine Learning.PDF by Yale Chang (11701611)

“…We therefore developed and evaluated retrospectively a machine learning model based on the XGBoost (XGB) algorithm which runs automatically on patient data from the electronic health record (EHR). …”

Image_1_Establishment of a novel lysosomal signature for the diagnosis of gastric cancer with in-vitro and in-situ validation.tif by Qi Wang (22418)

“…</p>Methods<p>To this end, this study, by utilizing the transcriptomic as well as single cell data and integrating 20 mainstream machine-learning (ML) algorithms. We optimized an AI-based predictor for GC diagnosis. …”

Data Sheet 1_Real-world data-driven early warning system for risk-stratified liver injury in hospitalized COVID-19 patients—Machine learning models for clinical decision support.do... by Yuanguo Xiong (20135991)

“…Thirteen distinct machine learning (ML) algorithms were trained and benchmarked to construct an optimal risk stratification framework. …”

Table_1_iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.DOCX by Carles Rubio Maturana (17448078)

“…</p>Conclusion<p>The coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases.…”

Image_1_iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.TIFF by Carles Rubio Maturana (17448078)

“…</p>Conclusion<p>The coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases.…”

Image_2_iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.TIFF by Carles Rubio Maturana (17448078)

“…</p>Conclusion<p>The coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases.…”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…</li><li>The dataframe of extracted colour features from all leaf images and lab variables (ecophysiological predictors and variables to be predicted)</li><li>Set of scripts used for image pre-processing, features extraction, data analytsis, visualization and Machine learning algorithms training, using ImageJ, R and Python.…”