Cultural Competence

Benefits, Pitfalls, and Potential Bias in Health Care AI.

As the health care industry adopts artificial intelligence, machine learning, and other modeling techniques, it is seeing benefits to both patient outcomes and cost reduction; however, it needs to be cognizant of and ensure proper management of the risks, including bias. Lessons learned from other industries may provide a framework for acknowledging and managing data, machine, and human biases tha...

On the Potential for Open-Endedness in Neural Networks.

Natural evolution gives the impression of leading to an open-ended process of increasing diversity and complexity. If our goal is to produce such open-endedness artificially, this suggests an approach driven by evolutionary metaphor. On the other hand, techniques from machine learning and artificial intelligence are often considered too narrow to provide the sort of exploratory dynamics associated...

Engineering Bias in AI.

After working at Apple designing circuits and signal processing algorithms for products including the first iPad, Timnit Gebru (Figure 1) received her...

Penalized PET Reconstruction Using Deep Learning Prior and Local Linear Fitting.

Motivated by the great potential of deep learning in medical imaging, we propose an iterative positron emission tomography reconstruction framework us...

Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk Differences for Lung Cancer Mortality by Emergency Presentation.

In this paper, we propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for...

Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?

The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing...

Estimating a Bias in ICD Encodings for Billing Purposes.

ICD encoded diagnoses are a popular criterion for eligibility algorithms for study cohort recruitment. However, "official" ICD encoded diagnoses used ...

Chemical-gene relation extraction using recursive neural network.

In this article, we describe our system for the CHEMPROT task of the BioCreative VI challenge. Although considerable research on the named entity reco...

Expectations for the Next Generation of Simulated Patients Born from Thoughtful Anticipation of Artificial Intelligence-Equipped Robot.

It is predicted that in the near future robot simulated patients (SPs) will come into use. Through the impressions of five SPs about robot SPs, we exp...

Computer-Aided Diagnosis of Lung Nodules in Computed Tomography by Using Phylogenetic Diversity, Genetic Algorithm, and SVM.

Lung cancer is pointed as the major cause of death among patients with cancer throughout the world. This work is intended to develop a methodology for...

[Effects of Soil Microbial Diversity on the Phosphate Fraction in the Rhizosphere of in the Yeyahu Wetland in Beijing, China].

In this research, microorganisms in rhizosphere/non-rhizosphere soils of in the Yeyahu Wetland were studied. A sequential extraction procedure was us...

Impact of Clinical Parameters in the Intrahost Evolution of HIV-1 Subtype B in Pediatric Patients: A Machine Learning Approach.

Determining the factors modulating the genetic diversity of HIV-1 populations is essential to understand viral evolution. This study analyzes the rela...

Feature selection using a one dimensional naïve Bayes' classifier increases the accuracy of support vector machine classification of CDR3 repertoires.

MOTIVATION: Somatic DNA recombination, the hallmark of vertebrate adaptive immunity, has the potential to generate a vast diversity of antigen recepto...

GI-SVM: A sensitive method for predicting genomic islands based on unannotated sequence of a single genome.

Genomic islands (GIs) are clusters of functionally related genes acquired by lateral genetic transfer (LGT), and they are present in many bacterial ge...

Alignment-Free Methods for the Detection and Specificity Prediction of Adenylation Domains.

Identifying adenylation domains (A-domains) and their substrate specificity can aid the detection of nonribosomal peptide synthetases (NRPS) at genome...