STDs

Predicting Hydrocarbon Primary Biodegradation in Soil and Sediment Systems Using System Parameterization and Machine Learning.

Technical complexity associated with biodegradation testing, particularly for substances of unknown or variable composition, complex reaction products, or biological materials (UVCB), necessitates the advancement of non-testing methods such as quantitative structure-property relationships (QSPRs). Models for describing the biodegradation of petroleum hydrocarbons (HCs) have been previously develop...

Going to extremes: progress in exploring new environments for novel antibiotics.

The discoveries of penicillin and streptomycin were pivotal for infection control with the knowledge subsequently being used to enable the discovery of many other antibiotics currently used in clinical practice. These valuable compounds are generally derived from mesophilic soil microorganisms, predominantly Streptomyces species. Unfortunately, problems with the replication of results suggested th...

Comparison of Machine Learning Algorithms for Heartbeat Detection Based on Accelerometric Signals Produced by a Smart Bed.

This work aims to compare the performance of Machine Learning (ML) and Deep Learning (DL) algorithms in detecting users' heartbeats on a smart bed. Ta...

Improving the performance of machine learning penicillin adverse drug reaction classification with synthetic data and transfer learning.

BACKGROUND: Machine learning may assist with the identification of potentially inappropriate penicillin allergy labels. Strategies to improve the perf...

Auto-segmentation of Adult-Type Diffuse Gliomas: Comparison of Transfer Learning-Based Convolutional Neural Network Model vs. Radiologists.

Segmentation of glioma is crucial for quantitative brain tumor assessment, to guide therapeutic research and clinical management, but very time-consum...

Screening oral drugs for their interactions with the intestinal transportome via porcine tissue explants and machine learning.

In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the development of oral drugs with greater bioavailabi...

Nanozyme-induced deep learning-assisted smartphone integrated colorimetric and fluorometric dual-mode for detection of tetracycline analogs.

In this work, a colorimetric and fluorescent dual-mode probe controlled by NH-MIL-88 B (Fe, Ni) nanozymes was developed to visually detect tetracyclin...

A hope for ineffective antibiotics to return to treatment: investigating the anti-biofilm potential of melittin alone and in combination with penicillin and oxacillin against multidrug resistant-MRSA and -VRSA.

BACKGROUND: The emergence and rapid spread of multi-drug resistant (MDR) bacterial strains, such as methicillin-resistant (MRSA) and vancomycin-resis...

Predicting Penicillin Allergy: A United States Multicenter Retrospective Study.

BACKGROUND: Using the reaction history in logistic regression and machine learning (ML) models to predict penicillin allergy has been reported based o...

Predicting cervical intraepithelial neoplasia and determining the follow-up period in high-risk human papillomavirus patients.

PURPOSE: Despite strong efforts to promote human papillomavirus (HPV) vaccine and cervical cancer screening, cervical cancer remains a threat to women...

Will it run?-A proof of concept for smoke testing decentralized data analytics experiments.

The growing interest in data-driven medicine, in conjunction with the formation of initiatives such as the European Health Data Space (EHDS) has demon...

Cases of Monkeypox show highly-overlapping co-infection with HIV and syphilis.

PURPOSE: Ongoing Monkeypox (MPX) outbreaks in countries outside Africa have unique characteristics. However, data on cohorts of confirmed cases in Chi...

Use of a humanoid robot for auditory psychophysical testing.

Tasks in psychophysical tests can at times be repetitive and cause individuals to lose engagement during the test. To facilitate engagement, we propos...

Drug review process advancement and required manufacturer and contract research oraganization responses.

The United States Senate passed the "FDA Modernization Act 2.0." on September 29, 2022. Although the effectiveness of this Bill, which aims to elimina...

Performance Analysis in Children of Traditional and Deep Learning CT Lung Nodule Computer-Aided Detection Systems Trained on Adults.

Although primary lung cancer is rare in children, chest CT is commonly performed to assess for lung metastases in children with cancer. Lung nodule c...

Development and validation of a fully automated 2-dimensional imaging system generating body condition scores for dairy cows using machine learning.

Monitoring body condition score (BCS) is a useful management tool to estimate the energy reserves of an individual cow or a group of cows. The aim of ...

Leveraging automated approaches to categorize birth defects from abstracted birth hospitalization data.

BACKGROUND: The Surveillance for Emerging Threats to Pregnant People and Infants Network (SET-NET) collects data abstracted from medical records and b...

Preclinical efficacy of a cell division protein candidate gonococcal vaccine identified by artificial intelligence.

Vaccines to curb the global spread of multidrug-resistant gonorrhea are urgently needed. Here, 26 vaccine candidates identified by an artificial intel...

A White-Box Testing for Deep Neural Networks Based on Neuron Coverage.

With the introduction of neuron coverage as a testing criterion for deep neural networks (DNNs), covering more neurons to detect more internal logic o...

Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.

OBJECTIVES: To develop and validate a multiparametric MRI-based radiomics model with optimal oversampling and machine learning techniques for predicti...