Sepsis

Towards Fluorescent-Tag-Less Viral Titration: Automated Estimation of Cell-Size Distribution and Infection Level from Phase-Contrast Microscopy Using Deep Learning and Transfer Learning.

Automated detection of infected insect cells is one of the crucial tasks in the field of recombinant protein production and vaccine development. The major challenge lies in manual segmentation of cells and quantifying cell size distribution is tedious and requires extensive effort. While such assessment of the infection levels is possible through fluorescent imaging, it requires tagging the expres...

Time-varying compartmental models with neural networks for pandemic infection forecasting.

The emergence and spread of deadly pandemics has repeatedly occurred throughout history, causing widespread infections and life loss. Forecasting the progression of pandemics is crucial for decision-makers to achieve its mitigation. This predictive task constitutes a challenge due to the non-stationary nature of pandemics, and changes in adopted policies and social reactions to them. Motivated by ...

Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning Techniques

Malaria parasites pose a significant global health burden, causing widespread suffering and mortality. Detecting malaria infection accurately is cru...

PANDORA: Deep graph learning based COVID-19 infection risk level forecasting

COVID-19 as a global pandemic causes a massive disruption to social stability that threatens human life and the economy. Policymakers and all elemen...

Unravelling the metabolic landscape of cutaneous melanoma: Insights from single-cell sequencing analysis and machine learning for prognostic assessment of lactate metabolism.

This manuscript presents a comprehensive investigation into the role of lactate metabolism-related genes as potential prognostic markers in skin cutan...

Application of AI in urolithiasis risk of infection: a scoping review.

INTRODUCTION: Artificial intelligence and machine learning are the new frontier in urology; they can assist the diagnostic work-up and in prognosticat...

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protei...

Clinician perspectives on how situational context and augmented intelligence design features impact perceived usefulness of sepsis prediction scores embedded within a simulated electronic health record.

OBJECTIVE: Obtain clinicians' perspectives on early warning scores (EWS) use within context of clinical cases.

Machine Learning for Clinical Decision Support of Acute Streptococcal Pharyngitis: A Pilot Study.

BACKGROUND: Group A Streptococcus (GAS) is the predominant bacterial pathogen of pharyngitis in children. However, distinguishing GAS from viral phary...

Machine learning reveals ferroptosis features and a novel ferroptosis classifier in patients with sepsis.

OBJECTIVE: Sepsis is an organ malfunction disease that may become fatal and is commonly accompanied by severe complications such as multiorgan dysfunc...

Automatically pre-screening patients for the rare disease aromatic l-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population.

OBJECTIVES: Electronic health record (EHR) data may facilitate the identification of rare diseases in patients, such as aromatic l-amino acid decarbox...

An infection prediction model developed from inpatient data can predict out-of-hospital COVID-19 infections from wearable data when controlled for dataset shift

The COVID-19 pandemic highlighted the importance of early detection of illness and the need for health monitoring solutions outside of the hospital se...

Where do doctors disagree? Characterizing Decision Points for Safe Reinforcement Learning in Choosing Vasopressor Treatment.

In clinical settings, domain experts sometimes disagree on optimal treatment actions. These "decision points" must be comprehensively characterized, a...

Emulation of a Target Trial to Estimate the Effect of Selective Serotonin Reuptake Inhibitors on the Development of Antimicrobial-Resistant Infections using Electronic Health Record Data and Causal Machine Learning.

Antimicrobial resistance is a significant public health concern. The use of selective serotonin reuptake inhibitors (SSRIs), medications commonly pres...

Enhancing Antibiotic Stewardship: A Machine Learning Approach to Predicting Antibiotic Resistance in Inpatient Care.

Antibiotics have been crucial in advancing medical treatments, but the growing threat of antibiotic resistance challenges these achievements and empha...

Evidence from Machine Learning, Diagnostic Hub Genes in Sepsis and Diagnostic Models based on Xgboost Models, Novel Molecular Models for the Diagnosis of Sepsis.

BACKGROUND: Systemic multi-organ dysfunction resulting from dysregulated immune responses in the host triggered by microbial infection or other factor...

[Research progress of artificial intelligence technology in early diagnosis of sepsis].

Sepsis is caused by infection, which can ultimately lead to multiple organ dysfunction and even life-threatening. Early recognition and early treatmen...

DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.

BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 ...

Diagnostic performance of machine-learning algorithms for sepsis prediction: An updated meta-analysis.

BACKGROUND: Early identification of sepsis has been shown to significantly improve patient prognosis.

[The efficacy analysis of neurosurgical robot-assisted DBS in the treatment of elderly Parkinson's disease].

To investigate the surgical efficacy of neurosurgery robot deep brain stimulation(DBS) in the treatment of elderly Parkinson's disease(PD). The clin...