Practice Management

Screening and validation of long non-coding RNAs associated with colorectal cancer based on random forest and LASSO regression algorithm.

OBJECTIVE: Colorectal cancer (CRC) ranks as the third most prevalent contributor to global disease burden and represents the second highest mortality rate among all malignancies worldwide. Long non-coding RNAs (lncRNAs) are a new class of regulatory RNAs, which play a crucial role in the occurrence and development of colorectal cancer. Therefore, it is potentially important to use bioinformatics a...

Artificial Intelligence to Support Qualitative Data Analysis: Promises, Approaches, Pitfalls.

How can artificial intelligence (AI) be used to support qualitative data analysis (QDA)? To address this question, the authors conducted 3 scholarly activities. First, they used a readily available large language model, ChatGPT-4, to analyze 3 existing narrative datasets (February 2024). ChatGPT generated accurate brief summaries; for all other attempted tasks the initial prompt failed to produce ...

Decoding the interactions and functions of non-coding RNA with artificial intelligence.

In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRN...

Self-Driving and Detachable Lab-Microrobots Tailor Drug Delivery for Closed-Loop Stimulation of the Antitumor Immune Cycle.

Hypoxia arises in most solid tumors with insufficient blood flow, which hinders the delivery and efficacy of therapeutic agents to tumors. In this wor...

Prediction of Acute Kidney Injury in Critically ill Patients with Community-Acquired Pneumonia Using Machine Learning.

BackgroundThe incidence of acute kidney injury (AKI) is increased in patients with community-acquired pneumonia (CAP), contributing to poor outcomes i...

From neurotoxicity to neuroprotection: Rethinking GABAR-targeting anesthetics.

The brain growth spurt (BGS) represents a pivotal window in neurodevelopment, defined by rapid neurogenesis, heightened synaptogenesis, and the dynami...

Classifying Stereotactic Radiosurgery Patients by Primary Diagnosis Using Natural Language Processing of Clinical Notes.

PURPOSE: Accurate identification of the primary tumor diagnosis of patients who have undergone stereotactic radiosurgery (SRS) from electronic health ...

Real-time automated billing for tobacco treatment: developing and validating a scalable machine learning approach.

OBJECTIVES: To develop CigStopper, a real-time, automated medical billing prototype designed to identify eligible tobacco cessation care codes, thereb...

Updates on inherited arrhythmia syndromes (Brugada syndrome, long QT syndrome, CPVT, ARVC).

The inherited arrhythmia (IA) syndromes are a group of rare and complex conditions that may predispose individuals to ventricular arrhythmias and sudd...

Predicting expression-altering promoter mutations with deep learning.

Only a minority of patients with rare genetic diseases are currently diagnosed by exome sequencing, suggesting that additional unrecognized pathogenic...

Immunogenic cell death biomarkers for sepsis diagnosis and mechanism via integrated bioinformatics.

Immunogenic cell death (ICD) has been implicated in sepsis, a condition with high mortality, through mechanisms involving endoplasmic reticulum stress...

CytoLNCpred-a computational method for predicting cytoplasm associated long non-coding RNAs in 15 cell-lines.

The function of long non-coding RNA (lncRNA) is largely determined by its specific location within a cell. Previous methods have used noisy datasets, ...

Parvalbumin neurons and cortical coding of dynamic stimuli: a network model.

Cortical circuits feature both excitatory and inhibitory cells that underlie the encoding of dynamic sensory stimuli, e.g., speech, music, odors, and ...

Construction of exosome non-coding RNA feature for non-invasive, early detection of gastric cancer patients by machine learning: a multi-cohort study.

BACKGROUND AND OBJECTIVE: Gastric cancer (GC) remains a prevalent and preventable disease, yet accurate early diagnostic methods are lacking. Exosome ...

Machine learning for predicting medical outcomes associated with acute lithium poisoning.

The use of machine learning algorithms and artificial intelligence in medicine has attracted significant interest due to its ability to aid in predict...

Definer: A computational method for accurate identification of RNA pseudouridine sites based on deep learning.

Pseudouridine is an important modification site, which is widely present in a variety of non-coding RNAs and is involved in a variety of important bio...

Advancing personalized, predictive, and preventive medicine in bladder cancer: a multi-omics and machine learning approach for novel prognostic modeling, immune profiling, and therapeutic target discovery.

OBJECTIVE: This study aimed to identify and analyze immunogenic cell death (ICD)-related multi-omics features in bladder cancer (BLCA) using single-ce...

AI-driven cybersecurity framework for software development based on the ANN-ISM paradigm.

With the increasing reliance on software applications, cybersecurity threats have become a critical concern for developers and organizations. The answ...

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study.

BACKGROUND: Congestive heart failure (CHF) is a common cause of hospital admissions. Medical records contain valuable information about CHF, but manua...

Low-cost algorithms for clinical notes phenotype classification to enhance epidemiological surveillance: A case study.

OBJECTIVE: Our study aims to enhance epidemic intelligence through event-based surveillance in an emerging pandemic context. We classified electronic ...