Sepsis

Review on electrochemical sensors for anticancer drug susceptibility testing.

Anticancer drug susceptibility tests play an essential role in areas such as drug development, pharmacokinetic research, and precision oncology. Across these tests, the methods that are traditionally used for gauging the drug effect-by determining the cell viability of in vitro cell models after drug exposure-are commonly time-consuming and limited to end-point detection. In this regard, electroch...

Development of a predictive model for eosinophilia in patients treated with ampicillin/sulbactam or piperacillin/tazobactam.

AIM: We aim to identify risk factors for antibiotic-induced eosinophilia in hospitalized patients receiving penicillin/beta-lactamase inhibitor therapy and to develop a machine learning-enhanced predictive risk-scoring model. METHODS: A retrospective cohort study was conducted involving 490 hospitalized patients treated with intravenous ampicillin/sulbactam or piperacillin/tazobactam. After applyi...

Effective alternative strategies to combat challenges associated with MDR bacterial infections: Drug repurposing, role of artificial intelligence, and novel therapeutic options.

Antibiotic failure has emerged as a critical global health concern, driven by a combination of factors including the stagnation in the discovery of ne...

Ligand-based prediction of anti-bacterial compounds: Overcoming class imbalance in molecular data.

In the emergence of pan-drug-resistant bacteria, there is an urgent demand for the discovery of structurally novel antibiotics. While traditional drug...

Authors reply: "How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach".

Utility of Baseline Pathological, Neuroimaging and Clinical Markers for Prognosis in Early Parkinson's Disease.

BackgroundCurrently, prognosis of Parkinson's Disease (PD) is limited. Emerging literature highlights potential of multi-modal biomarkers and neuroima...

Homogeneous multi-antibiotics residual identification in various actual water via SERS spectra multilayer perceptron algorithm combined with Gaussian kernel density estimation data augmentation.

BACKGROUND: Antibiotic residues pose varying degrees of potential hazards to the water environment and human health due to their diverse types. Surfac...

Machine learning-accelerated 1H NMR quantification for bioprocess metabolite monitoring in monoclonal antibody production.

Monitoring of metabolite dynamics during cell culture process is crucial for ensuring consistent monoclonal antibody (mAb) yield and quality. While pr...

Predictive value of dynamic creatinine cumulative exposure and trajectory classification onmortality in severe acute pancreatitis: a multicenter retrospective cohort study.

AIMS: This study aims to evaluate the predictive value of cumulative creatinine exposure (CumCr) and dynamic creatinine trajectories for severe acute ...

The application of machine learning in the evaluation of urinary tract infections incidence in patients in a Nursing and Treatment Facility.

BACKGROUND: Urinary tract infection (UTI) is a serious problem in the healthcare system. It is caused by bacteria from the gastrointestinal tract. The...

Augmentation Models of Stem Cell Culture Data for the Application of Machine Learning.

Bioprocesses for stem cell-based therapeutics are resource- and time-intensive, hindering the generation of sufficient data for machine learning-infor...

Letter to the editor: "How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a behavioural artificial intelligence technology (BAIT) approach".

Behavioural Artificial Intelligence Technology (BAIT) has recently been proposed to codify expert reasoning for sepsis surveillance. We provide prelim...

Bioelectrochemical mitigation of soil antibiotic resistance: Disruption of bacteriophage transmission and resistant hosts.

The proliferation of antibiotic resistance genes (ARGs) in environment poses a threat to global public health. Although microbial fuel cell (MFC) has ...

Prediction of Short-Term Postoperative Complications Following Open Reduction Internal Fixation of Ankle Fractures.

BACKGROUND: Minimizing postoperative complications is imperative to improving patient outcomes. The purpose of this investigation is to develop machin...

Deep machine learning methods for Parkinson's disease diagnosis: a new direction in decision-making systems.

Parkinson's disease (PD) is a progressive neurodegenerative disorder primarily characterized by the gradual loss of dopamine-producing neurons in the ...

Nanomotion-based technology for rapid antibiotic susceptibility testing among adult patients admitted to a tertiary-care hospital with Gram-negative bacteraemia: a prospective, single arm, comparative diagnostic accuracy study.

OBJECTIVE: Investigate performances and turnaround time of Resistell Phenotech antibiotic susceptibility testing (AST), a device using the new nanomot...

Using precision medicine methods to identify disease stages for chronic limb-threatening ischemia in participants of the BEST-CLI trial.

BACKGROUND: Chronic limb-threatening ischemia (CLTI), the most severe form of peripheral artery disease, is associated with a high risk of limb loss. ...

Machine learning-based integration develops a lactate metabolism related gene signature for improving outcomes in pancreatic ductal adenocarcinoma.

OBJECTIVES: Given its high global mortality rate, pancreatic ductal adenocarcinoma (PDAC) remains a significant area of investigation. However, a robu...

Early prediction of septic shock in ICU patients using machine learning: development, external validation, and explainability with SHAP.

BACKGROUND: Septic shock is a severe and life-threatening complication of sepsis associated with high mortality. Early identification remains challeng...

Machine learning-assisted sensing platform for simultaneous and visual detection of tetracycline hydrochloride and ofloxacin.

Antibiotics are essential in modern medicine; however, their overuse and improper disposal have caused significant environmental contamination, which ...