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Hyperspectral Imaging and Deep Learning for Quality and Safety Inspection of Fruits and Vegetables: A Review.

Quality inspection of fruits and vegetables linked to food safety monitoring and quality control. Tr...

Is the energy quota trading policy a solution to carbon inequality in China? Evidence from double machine learning.

Implementing China's energy quota trading policy, as a typical market-based environmental regulation...

Designing Clinical Trials for Patients With Rare Cancers: Connecting the Zebras.

The field of rare cancer research is rapidly transforming, marked by significant progress in clinica...

Leveraging multi-modal feature learning for predictions of antibody viscosity.

The shift toward subcutaneous administration for biologic therapeutics has gained momentum due to it...

A potential supplemental indication of dipyridamole for contraception: Dipyridamole inhibits mouse sperm fertilization capacity in vitro.

The inhibition of sperm cAMP and ATP levels, using an FDA-approved medication, may impair sperm moti...

A deep learning-based approach for the detection of cucumber diseases.

Cucumbers play a significant role as a greenhouse crop globally. In numerous countries, they are fun...

Artificial intelligence to predict treatment response in rheumatoid arthritis and spondyloarthritis: a scoping review.

To analyse the types and applications of artificial intelligence (AI) technologies to predict treatm...

Machine learning-based in-silico analysis identifies signatures of lysyl oxidases for prognostic and therapeutic response prediction in cancer.

BACKGROUND: Lysyl oxidases (LOX/LOXL1-4) are crucial for cancer progression, yet their transcription...

Updates in Neonatal Seizures.

Neonatal seizures are a common medical emergency, necessitating prompt treatment. The most common et...

Generalizability of FDA-Approved AI-Enabled Medical Devices for Clinical Use.

IMPORTANCE: The primary objective of any newly developed medical device using artificial intelligenc...

Deciphering aging-associated prognosis and heterogeneity in gastric cancer through a machine learning-driven approach.

Gastric cancer (GC) is a prevalent malignancy with a high mortality rate and limited treatment optio...

DICTrank Is a Reliable Dataset for Cardiotoxicity Prediction Using Machine Learning Methods.

Drug-induced cardiotoxicity (DICT) is a significant challenge in drug development and public health....

Future horizons in diabetes: integrating AI and personalized care.

Diabetes is a global health crisis with rising incidence, mortality, and economic burden. Traditiona...

Artificial intelligence in chronic kidney disease management: a scoping review.

Chronic kidney disease (CKD) is a major public health problem worldwide associated with cardiovascu...

Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.

Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, ye...

Personalized prediction of psoriasis relapse post-biologic discontinuation: a machine learning-driven population cohort study.

BACKGROUND: Identifying the risk of psoriasis relapse after discontinuing biologics can help optimiz...

Reducing hepatitis C diagnostic disparities with a fully automated deep learning-enabled microfluidic system for HCV antigen detection.

Viral hepatitis remains a major global health issue, with chronic hepatitis B (HBV) and hepatitis C ...

Estimating patient-specific organ doses from head and abdominal CT scans via machine learning with optimized regulation strength and feature quantity.

PURPOSE: This study aims to investigate estimation of patient-specific organ doses from CT scans via...

Rapid and accurate identification and quantification of Lycium barbarum L. components: Integrating deep learning and NMR for nutritional assessment.

Lycium barbarum L. (L. barbarum), revered for its nutritional and commercial value, exhibits variabl...

A comprehensive review of neurotransmitter modulation via artificial intelligence: A new frontier in personalized neurobiochemistry.

The deployment of artificial intelligence (AI) is revolutionizing neuropharmacology and drug develop...

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