Practice Management

Predictive coding with spiking neural networks: A survey.

In this article, we review a class of neuro-mimetic computational models that we place under the label of spiking predictive coding. Specifically, we review the general framework of predictive processing in the context of neurons that emit discrete action potentials, i.e., spikes. Theoretically, we structure our survey around how prediction errors are represented. This results in an organization i...

Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.

Type 2 diabetes is a polygenic, heterogeneous disease affecting over 530 million individuals worldwide, a number projected to rise to 1.3 billion by 2050. Genome-wide association studies have identified over 1200 loci associated with type 2 diabetes, yet only a modest proportion of disease heritability has been explained, and most risk variants lie in non-coding regions, complicating biological in...

BRAIN-MAGNET: A functional genomics atlas for interpretation of non-coding variants.

Genome-wide assessment of genetic variation is becoming routine in genetics, yet functional interpretation of non-coding single nucleotide variants in...

Human versus machine: A comparative analysis of qualitative coding by humans and ChatGPT-4.

Generative artificial intelligence (AI) applications are becoming increasingly influential in psychology training, practice, and research. In this stu...

Accelerometer-measured intensity-specific physical activity, genetic susceptibility, and back pain risk: a UK Biobank cohort study.

BACKGROUND CONTEXT: Current clinical guidelines lack clear, quantitative recommendations on intensity-specific physical activity (PA) levels for preve...

A survey on neuro-mimetic deep learning via predictive coding.

Artificial intelligence (AI) is rapidly becoming one of the key technologies of this century. The majority of results in AI thus far have been achieve...

Off-the-Shelf Large Language Models for Guiding Pharmacoepidemiological Study Design.

This study aimed to assess the ability of two off-the-shelf large language models, ChatGPT and Gemini, to support the design of pharmacoepidemiologica...

Integrative machine learning approach to risk prediction for dementia and Alzheimer's disease.

Dementia, particularly Alzheimer's disease (AD), presents a growing global health challenge characterized by cognitive decline, behavioral changes, an...

Development and validation of a natural language processing system to assess quality of physician communication in prostate cancer consultations.

BACKGROUND: AUA guidelines for shared decision making (SDM) in prostate cancer recommend discussion of five content areas in consultations: (1) cancer...

Leveraging large language models to identify microcounseling skills in psychotherapy transcripts.

Objective: Microcounseling skills are fundamental to effective psychotherapy, yet manual coding is time- and resource-intensive. This study explores t...

Global genomics of Lactococcus lactis: horizontal gene transfer and intergenic variation drive multiple domestication and dairy adaptation.

INTRODUCTION: Lactococcus lactis is a crucial lactic acid bacterium of great economically significance for cheese product. The species exhibits wildly...

Advancing fungal phylogenetics: integrating modern sequencing, dark taxa discovery, and machine learning.

The study of fungal genetics has undergone transformative advancements in recent decades, profoundly reshaping our understanding of fungal diversity, ...

How machine learning on real world clinical data improves adverse event recording for endoscopy.

Endoscopic interventions are essential for diagnosing and treating gastrointestinal conditions. Accurate and comprehensive documentation is crucial fo...

Identification of a novel ferroptosis-induced immunogenic cell death related signature based on a machine learning framework in colorectal cancer.

BACKGROUND: Ferroptosis and immunogenic cell death play vital roles in colorectal cancer (CRC). The interplay between ferroptosis and immunogenic cell...

Language Models for Multilabel Document Classification of Surgical Concepts in Exploratory Laparotomy Operative Notes: Algorithm Development Study.

BACKGROUND: Operative notes are frequently mined for surgical concepts in clinical care, research, quality improvement, and billing, often requiring h...

Development and Validation of a Rule-Based Natural Language Processing Algorithm to Identify Falls in Inpatient Records of Older Adults: Retrospective Analysis.

BACKGROUND: In order to address fall underestimation by the International Classification of Diseases (ICD) in clinical settings, information from clin...

Cooperative coding of continuous variables in networks with sparsity constraint.

A hallmark of biological and artificial neural networks is that neurons tile the range of continuous sensory inputs and intrinsic variables with overl...

Machine learning for the prediction of urosepsis using electronic health record data.

Urosepsis, a medical condition resulting from the progression of urinary tract infection (UTI), is a leading cause of death in the US. Urosepsis occur...

Polar code construction by estimating noise using bald hawk optimized recurrent neural network model.

Polar codes are making significant progress in error-correcting coding due to their ability to reach the limit of the Shannon capacity of communicatio...

Using graph machine learning to identify functioning in patients with low back pain in terms of ICF.

As a comprehensive perspective on functioning is useful in patient assessments, the WHO developed the International Classification of Functioning, Dis...