What this AI epitope library means for vaccines, immunotherapy and biosensors

A new tool makes it possible to screen millions of tiny protein fragments and select those that can be recognized by the ...
Frontiers

Disease classification via interpretable machine learning based on multi-center routine coagulation test

This study aims to establish an interpretable disease classification model via machine learning and identify key features related to the disease to assist clinical disease diagnosis based on a ...
blockchain

XPENG P7+ AI-Driven Light Signals: Decoding Binary Messages and Autonomous Vehicle Trends

According to XPeng Motors (@XPengMotors), the XPENG P7+ electric vehicle showcased synchronized tail light flickers and a binary code '0101' display, hinting at advanced AI integration and ...
GitHub

binary-classification

This project is a full machine learning pipeline for Star/Galaxy classification using the SDSS dataset. It also contains a detailed report on the development and a DockerFile to easily replicate the ...
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
IEEE

Bi-SSFormer: An Ultralightweight Binary Spectral–Spatial Transformer for Hyperspectral Image Classification

Abstract: With the advancement of deep learning techniques, deep neural networks have progressively supplanted traditional machine learning methods for hyperspectral image (HSI) classification, ...
Scientific Research Publishing

Sen, P.C., Hajra, M. and Ghosh, M. (2019) Supervised Classification Algorithms in Machine Learning: A Survey and Review. In: Mandal, J.K. and Bhattacharya, D., Eds., Emerging ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Scientific Research Publishing

Haghish, E.F. and Czajkowski, N. (2023) Reconsidering False Positives in Machine Learning Binary Classification Models of Suicidal Behavior. Current Psychology, 43, 10117-10121.

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...
IEEE

Safe and Robust Binary Classification and Fault Detection Using Reinforcement Learning

Abstract: In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. This classifier is designed to ...