Results 81 to 90 of about 145,182 (282)

The Sociodemographic Biases in Machine Learning Algorithms: A Biomedical Informatics Perspective

Life
Artificial intelligence models represented in machine learning algorithms are promising tools for risk assessment used to guide clinical and other health care decisions.
Gillian Franklin, Rachel Stephens, Muhammad Piracha, Shmuel Tiosano, Frank Lehouillier, Ross Koppel, Peter L. Elkin   +6 more
doaj   +1 more source

Algorithms in the Workplace, an Unbiased Technology? [PDF]

Revista de Management Comparat International
This study analyses how biases may emerge in algorithms due to human intervention and explores the legal risks associated with these biases, conceptualising algorithm as a sufficiently detailed and systematic instruction of action to solve a ...
Lidia de la IGLESIA AZA
doaj   +1 more source

Semi-optimal Practicable Algorithmic Cooling

, 2011
Algorithmic Cooling (AC) of spins applies entropy manipulation algorithms in open spin-systems in order to cool spins far beyond Shannon's entropy bound.
L. J. Schulman, Tal Mor, Y. Elias, Yossi Weinstein, Yuval Elias   +4 more
core   +1 more source

Discovery and Targeted Proteomic Studies Reveal Striatal Markers Validated for Huntington's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Clinical trials for Huntington's disease (HD) enrolling persons before clinical motor diagnosis (CMD) lack validated biomarkers. This study aimed to conduct an unbiased discovery analysis and a targeted examination of proteomic biomarkers scrutinized by clinical validation. Methods Cerebrospinal fluid was obtained from PREDICT‐HD and
Daniel Chelsky, Cara Joyce, H. Jeremy Bockholt, Paul A. Rudnick, William H. Adams, Fiona McAllister, Justin W. Smock, Michael A. Newton, Jane S. Paulsen   +8 more
wiley   +1 more source

How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility

, 2018
Recommendation systems are ubiquitous and impact many domains; they have the potential to influence product consumption, individuals' perceptions of the world, and life-altering decisions. These systems are often evaluated or trained with data from users
Anderson C., Bennett J., Bottou L., Chander A, Dan-Dan Z., Jolliffe I., Lee D. D., Salakhutdinov R.   +7 more
core   +1 more source

Lessons Learned From a Delayed‐Start Trial of Modafinil for Freezing of Gait in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Freezing of gait (FOG) in people with Parkinson's disease (PwPD) is debilitating and has limited treatments. Modafinil modulates beta/gamma band activity in the pedunculopontine nucleus (PPN), like PPN deep brain stimulation. We therefore tested the hypothesis that Modafinil would improve FOG in PwPD.
Tuhin Virmani, Lakshmi Pillai, Reid D. Landes, Aliyah Glover, Shannon Doerhoff, Jennifer Kleiner, Mitesh Lotia, Rohit Dhall, Edgar Garcia‐Rill   +8 more
wiley   +1 more source

Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction

, 2018
As algorithms are increasingly used to make important decisions that affect human lives, ranging from social benefit assignment to predicting risk of criminal recidivism, concerns have been raised about the fairness of algorithmic decision making.
Grgić-Hlača, Nina, Gummadi, Krishna P., Redmiles, Elissa M., Weller, Adrian   +3 more
core   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Rethinking Artificial Intelligence: Algorithmic Bias and Ethical Issues| How Gender and Type of Algorithmic Group Discrimination Influence Ratings of Algorithmic Decision Making

International Journal of Communication, 2023
Algorithms frequently discriminate against certain groups, and people generally reject such unfairness. However, people sometimes display an egocentric bias when choosing between fairness rules.
Sonja Utz
doaj   +2 more sources

A Comprehensive Review of AI Techniques for Addressing Algorithmic Bias in Job Hiring

AI
The study comprehensively reviews artificial intelligence (AI) techniques for addressing algorithmic bias in job hiring. More businesses are using AI in curriculum vitae (CV) screening. While the move improves efficiency in the recruitment process, it is
Elham Albaroudi, Taha Mansouri, Ali Alameer   +2 more
doaj   +1 more source