Public Health & Policy

Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study.

BACKGROUND: Influenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often struggle to predict influenza outbreaks in an accurate and timely manner. Big data and modern technology have offered new modalities for disease surveillance and prediction. Influenza-like illness can serve as a valuable surveillance tool for emerging resp...

Sooty Mold Detection on Citrus Tree Canopy Using Deep Learning Algorithms.

Sooty mold is a common disease found in citrus plants and is characterized by black fungi growth on fruits, leaves, and branches. This mold reduces the plant's ability to carry out photosynthesis. In small leaves, it is very difficult to detect sooty mold at the early stages. Deep learning-based image recognition techniques have the potential to identify and diagnose pest damage and diseases such ...

Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes.

Although most pregnancies result in a good outcome, complications are not uncommon and can be associated with serious implications for mothers and bab...

Evaluating the Use of a Robot in a Hematological Intensive Care Unit: A Pilot Study.

The aim of the SYRIACA project was to test the capability of a social robot to perform specific tasks in healthcare settings, reducing infection risks...

Attenuative effects of collagen peptide from milkfish () scales on ovariectomy-induced osteoporosis.

Osteoporosis is characterized by low bone mass, bone microarchitecture disruption, and collagen loss, leading to increased fracture risk. In the curre...

Early monitoring-to-warning Internet of Things system for emerging infectious diseases via networking of light-triggered point-of-care testing devices.

Early monitoring and warning arrangements are effective ways to distinguish infectious agents and control the spread of epidemic diseases. Current tes...

Challenges and opportunities of big data analytics in healthcare.

Data science is an interdisciplinary discipline that employs big data, machine learning algorithms, data mining techniques, and scientific methodologi...

Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.

: To evaluate the comparative effectiveness of treatments, a randomized clinical trial remains the gold standard but can be challenged by a high cost,...

Deep Learning-Based Model for Automatic Assessment of Anterior Angle Chamber in Ultrasound Biomicroscopy.

OBJECTIVE: The goal of the work described here was to develop and assess a deep learning-based model that could automatically segment anterior chamber...

Beyond SEP-1 Compliance: Assessing the Impact of Antibiotic Overtreatment and Fluid Overload in Suspected Septic Patients.

BACKGROUND: The Centers for Medicare and Medicaid Services (CMS) developed the Severe Sepsis and Septic Shock Performance Measure bundle (SEP-1) metri...

Firearm violence exposure and health in 2 national samples of Black and American Indian/Alaska Native adults.

Exposure to firearm violence is widespread and disproportionately experienced by communities of color, with implications for broad health disparities....

Enhanced phenotypes for identifying opioid overdose in emergency department visit electronic health record data.

BACKGROUND: Accurate identification of opioid overdose (OOD) cases in electronic healthcare record (EHR) data is an important element in surveillance,...

Effectiveness of an artificial intelligence-based training and monitoring system in prevention of nosocomial infections: A pilot study of hospital-based data.

This work describes a novel artificial intelligence-based training and monitoring system (AITMS) that was used to control and prevent nosocomial infec...

Rapid Discrimination of ST175 Isolates Involved in a Nosocomial Outbreak Using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy Coupled with Machine Learning.

The goal of this study was to evaluate matrix-assisted laser desorption ionization-iime of flight mass spectrometry (MALDI-TOF MS) and Fourier-transfo...

Comprehensive study of algal blooms variation in Jiaozhou Bay based on google earth engine and deep learning.

The Jiaozhou Bay ecosystem, a crucial marine ecosystem in China, has been plagued by frequent harmful algal blooms as due to deteriorating water quali...

Fuzzy entropy DEMATEL inference system for accurate and efficient cardiovascular disease diagnosis.

The global population is at risk from both communicable and non-communicable deadly diseases, including cardiovascular disease. Early detection and pr...

Effect of Peritoneal Interposition Flap to Prevent Symptomatic Lymphoceles in Robot-Assisted Radical Prostatectomy with Pelvic Lymphadenectomy: A Meta-Analysis and Systematic Review.

This systematic review and meta-analysis investigated whether peritoneal interposition flap (PIF) prevent lymphocele formation after robot-assisted r...

Prediction of suicidal ideation in children and adolescents using machine learning and deep learning algorithm: A case study in South Korea where suicide is the leading cause of death.

BACKGROUND: Korea has the highest suicide rate among Organisation for Economic Co-operation and Development (OECD) countries. Consequently, central an...

Cheminformatics and machine learning approaches for repurposing anti-viral compounds against monkeypox virus thymidylate kinase.

One of the emerging epidemic concerns is Monkeypox disease which is spreading globally. This disease is caused by the monkeypox virus (MPXV), with an ...

Imagining machine vision: Four visual registers from the Chinese AI industry.

Machine vision is one of the main applications of artificial intelligence. In China, the machine vision industry makes up more than a third of the nat...