Nature

A comparative study of machine learning models for microbiome-based diagnosis and multi-class staging of colorectal cancer

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...
Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
IEEE

Comparison of Machine Learning Algorithms for Predicting Crime Hotspots

Abstract: Crime prediction is of great significance to the formulation of policing strategies and the implementation of crime prevention and control. Machine learning is the current mainstream ...
GitHub

Machine Learning project for classifying Iris flower species using Python and K-Nearest Neighbors (KNN).

This project uses Machine Learning to classify Iris flowers into three different species based on their physical measurements. The classification is performed using the K-Nearest Neighbors (KNN) ...
Frontiers

Enhanced differentiation of breast lesions through integration of microvascular flow imaging and machine learning algorithms

Breast cancer diagnosis relies on imaging, yet conventional Doppler ultrasound possesses limitations in visualizing tumor microvasculature. This study aimed to compare Microvascular Flow imaging ...
LinkedIn

Arif Alam’s Post

𝗠𝗼𝘀𝘁 𝗯𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀 𝗹𝗲𝗮𝗿𝗻 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘁𝗵𝗲 ...
LinkedIn

Data Science’s Post

This visual perfectly highlights how different algorithms fit data patterns and handle complexity. 📊 🔹 Linear Regression ️ Best for simple linear relationships between variables. 🔹 Stochastic ...

New algorithm identifies disease-linked changes in cells without prior training

A new algorithm could drive breakthroughs in understanding cancer, Alzheimer's disease and other potentially fatal conditions ...
IEEE

Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions

Abstract: Malware has emerged as a cyber security threat that continuously changes to target computer systems, smart devices, and extensive networks with the development of information technologies.
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
GitHub

Fish Species Survival Prediction Using IoT and Machine Learning

This repository presents our Final Year Project (FYP), which focuses on developing an intelligent aquaculture monitoring and fish survival prediction system using Internet of Things (IoT), Edge ...
Journal of Medical Internet Research

Mortality Risk Prediction in Patients With Antimelanoma Differentiation–Associated, Gene 5 Antibody–Positive, Dermatomyositis–Associated Interstitial Lung Disease ...

Six ML algorithms (Extreme Gradient Boosting [XGBoost], logistic regression (LR), Light Gradient Boosting Machine [LightGBM], random forest [RF], support vector machine [SVM], and k-nearest neighbor ...