Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Deep Learning to Forecast Solar Irradiance Using a Six-Month UTSA SkyImager Dataset
Energies, 2018 Distributed PV power generation necessitates both intra-hour and day-ahead forecasting of solar irradiance. The UTSA SkyImager is an inexpensive all-sky imaging system built using a Raspberry Pi computer with camera.
Ariana Moncada +2 more
doaj +1 more source
, 2019 One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability. In this work, a practicable approach of gaining explainability of deep artificial neural networks (NN) using an ...
Huber, Marco F. +2 more
core +1 more source
Upfront Surgery or Neoadjuvant Chemotherapy for Colorectal Liver Metastases? A Machine-Learning Decision-Tree to Identify the Best Potential Policy [PDF]
, 2022 Simone Famularo +11 more
openalex +1 more source
Learning Invariants using Decision Trees
, 2015 15 pages, 2 ...
Krishna, Siddharth +2 more
openaire +2 more sources
Peptide Sequencing With Single Acid Resolution Using a Sub‐Nanometer Diameter Pore
Advanced Functional Materials, EarlyView.To sequence a single molecule of Aβ1−42–sodium dodecyl sulfate (SDS), the aggregate is forced through a sub‐nanopore 0.4 nm in diameter spanning a 4.0 nm thick membrane. The figure is a visual molecular dynamics (VMD) snapshot depicting the translocation of Aβ1−42–SDS through the pore; only the peptide, the SDS, the Na+ (yellow/green) and Cl− (cyan ...
Apurba Paul +8 more
wiley +1 more source
An investigation into machine learning approaches for forecasting spatio-temporal demand in ride-hailing service [PDF]
, 2017 In this paper, we present machine learning approaches for characterizing and forecasting the short-term demand for on-demand ride-hailing services. We propose the spatio-temporal estimation of the demand that is a function of variable effects related to ...
Cools, Mario +4 more
core
Comparison of decision tree with common machine learning models for prediction of biguanide and sulfonylurea poisoning in the United States: an analysis of the National Poison Data System [PDF]
, 2023 Omid Mehrpour +6 more
openalex +1 more source
Multiple Twinning in Nacre and Aragonite
Advanced Functional Materials, EarlyView.Electron backscatter diffraction map of a cluster of geologic aragonite, exhibiting single, double, and triple twins. The whole cluster is approximately 2 cm wide. Colors indicate crystal orientations, so that pixels where the a‐, b‐, and c‐axis is perpendicular to the image plane are green, red, and blue, respectively.
Connor A. Schmidt +7 more
wiley +1 more source
Deepfake Image Classification Using Decision (Binary) Tree Deep Learning
Journal of Sensor and Actuator NetworksThe unprecedented rise of deepfake technologies, leveraging sophisticated AI like Generative Adversarial Networks (GANs) and diffusion-based models, presents both opportunities and challenges in terms of digital media authenticity.
Mariam Alrajeh, Aida Al-Samawi
doaj +1 more source