Results 81 to 90 of about 1,710,361 (207)

Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development

Clinical and Translational Science
Despite increasing interest in using Artificial Intelligence (AI) and Machine Learning (ML) models for drug development, effectively interpreting their predictions remains a challenge, which limits their impact on clinical decisions.
A. V. Ponce-Bobadilla, Vanessa Schmitt, Corinna Maier, S. Mensing, S. Stodtmann   +4 more
semanticscholar   +1 more source

ML-NIC: accelerating machine learning inference using smart network interface cards

Frontiers in Computer Science
Low-latency inference for machine learning models is increasingly becoming a necessary requirement, as these models are used in mission-critical applications such as autonomous driving, military defense (e.g., target recognition), and network traffic ...
Raghav Kapoor, David C. Anastasiu, Sean Choi   +2 more
doaj   +1 more source

Probabilistic weather forecasting with machine learning

Nature
Weather forecasts are fundamentally uncertain, so predicting the range of probable weather scenarios is crucial for important decisions, from warning the public about hazardous weather to planning renewable energy use.
Ilan Price, Alvaro Sanchez-Gonzalez, Ferran Alet, Tom R. Andersson, A. El-Kadi, Dominic Masters, T. Ewalds, Jacklynn Stott, Shakir Mohamed, Peter W. Battaglia, Remi Lam, Matthew Willson   +11 more
semanticscholar   +1 more source

Optimization of two-wheeler Bike engine among three different designs using design of experiments

Heliyon
This research presents the results of a fin heat transfer study of three different models of the motorcycle engine. The objective of this study is to minimize the external body temperature because the optimum design will be found when the heat transfer ...
Manish Dadhich, Vikas Sharma, Gaurav Jain, K. Loganathan, V. Karunakaran, Mohamed Abbas, P. Subhashini   +6 more
doaj   +1 more source

Ethical and Bias Considerations in Artificial Intelligence (AI)/Machine Learning.

Modern Pathology
As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications and potential biases within such integrated AI models will require careful scrutiny.
Matthew G. Hanna, Liron Pantanowitz, Brian R. Jackson, Octavia Palmer, Shyam Visweswaran, Joshua Pantanowitz, Mustafa Deebajah, H. Rashidi   +7 more
semanticscholar   +1 more source

Comparative assessment of rainfall-based water level prediction using machine learning (ML) techniques

Ain Shams Engineering Journal
Machine learning (ML) techniques are rapidly emerging as effective tools in predicting complex hydrological processes. The present study aims to comparatively assess the efficacy of four machine learning algorithms – Multi-Layer Perceptron (MLP), Extreme
Azazkhan Ibrahimkhan Pathan, Lariyah Bte Mohd Sidek, Hidayah Bte Basri, Muhammad Yusuf Hassan, Muhammad Izzat Azhar Bin Khebir, Siti Mariam Binti Allias Omar, Mohd Hazri bin Moh Khambali, Adrián Morales Torres, Ali Najah Ahmed   +8 more
doaj   +1 more source

A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions

IEEE Access
Given the continually rising frequency of cyberattacks, the adoption of artificial intelligence methods, particularly Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL), has become essential in the realm of cybersecurity.
Merve Ozkan-okay, Erdal Akin, Ömer Aslan, S. Kosunalp, T. Iliev, I. Stoyanov, I. Beloev   +6 more
semanticscholar   +1 more source

Progress and Opportunities for Machine Learning in Materials and Processes of Additive Manufacturing

Advances in Materials
In recent years, there has been widespread adoption of machine learning (ML) technologies to unravel intricate relationships among diverse parameters in various additive manufacturing (AM) techniques. These ML models excel at recognizing complex patterns
Wei Long Ng, G. L. Goh, G. D. Goh, Jason Ten Jyi Sheuan, W. Y. Yeong   +4 more
semanticscholar   +1 more source

Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities

AIMS Public Health
In recent years, machine learning (ML) and deep learning (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications.
Anichur Rahman, Tanoy Debnath, Dipanjali Kundu, Md. Saikat Islam Khan, Airin Afroj Aishi, Sadia Sazzad, Mohammad Sayduzzaman, Shahab S. Band   +7 more
semanticscholar   +1 more source

Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

ACS Central Science
Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency—or even to unlock new catalytic activities not found in nature.
Jason Yang, Francesca-Zhoufan Li, Frances H. Arnold   +2 more
semanticscholar   +1 more source