Migraines

Efficient deep learning-based approach for malaria detection using red blood cell smears.

Malaria is an extremely malignant disease and is caused by the bites of infected female mosquitoes. This disease is not only infectious among humans, but among animals as well. Malaria causes mild symptoms like fever, headache, sweating and vomiting, and muscle discomfort; severe symptoms include coma, seizures, and kidney failure. The timely identification of malaria parasites is a challenging an...

The Ethical Stewardship of Artificial Intelligence in Chronic Pain and Headache: A Narrative Review.

PURPOSE OF REVIEW: As artificial intelligence (AI) and machine learning (ML) are becoming more pervasive in medicine, understanding their ethical considerations for chronic pain and headache management is crucial for optimizing their safety.

The potential use of artificial intelligence for venous thromboembolism prophylaxis and management: clinician and healthcare informatician perspectives.

Venous thromboembolism (VTE) is the leading cause of preventable death in hospitalized patients. Artificial intelligence (AI) and machine learning (ML...

Machine learning identifies factors most associated with seeking medical care for migraine: Results of the OVERCOME (US) study.

OBJECTIVE: Utilize machine learning models to identify factors associated with seeking medical care for migraine.

Improving HIV preexposure prophylaxis uptake with artificial intelligence and automation: a systematic review.

OBJECTIVES: To identify studies promoting the use of artificial intelligence (AI) or automation with HIV preexposure prophylaxis (PrEP) care and explo...

Diagnostic biomarker discovery from brain EEG data using LSTM, reservoir-SNN, and NeuCube methods in a pilot study comparing epilepsy and migraine.

The study introduces a new online spike encoding algorithm for spiking neural networks (SNN) and suggests new methods for learning and identifying dia...

Artificial intelligence and social media: (Appropriately) harnessing headache medicine's new arsenal in the 21st century.

Migraine aura discrimination using machine learning: an fMRI study during ictal and interictal periods.

Functional magnetic resonance imaging (fMRI) studies on migraine with aura are challenging due to the rarity of patients with triggered cases. This st...

A large language model-based generative natural language processing framework fine-tuned on clinical notes accurately extracts headache frequency from electronic health records.

OBJECTIVE: To develop a natural language processing (NLP) algorithm that can accurately extract headache frequency from free-text clinical notes.

Machine learning models help differentiate between causes of recurrent spontaneous vertigo.

BACKGROUND: Vestibular migraine (VM) and Menière's disease (MD) are two common causes of recurrent spontaneous vertigo. Using history, video-nystagmog...

Migraine headache (MH) classification using machine learning methods with data augmentation.

Migraine headache, a prevalent and intricate neurovascular disease, presents significant challenges in its clinical identification. Existing technique...

Inadequate Anti-Factor Xa Levels With Daily 40-mg Enoxaparin After Cardiac Surgery.

BACKGROUND: Cardiac surgery patients are at increased risk for venous thromboembolism (VTE). Prevention is the most critical strategy to reduce VTE-as...

Assessing risk factors associated with breakthrough early post-traumatic seizures in patients receiving phenytoin prophylaxis.

OBJECTIVE: Post-traumatic seizure (PTS) is a well-known complication of traumatic brain injury (TBI). The objective of this study was to identify risk...

Pharmacokinetics and coagulation biomarkers in children and adults with hemophilia A receiving emicizumab prophylaxis every 1, 2, or 4 weeks.

BACKGROUND: Emicizumab is a bispecific antibody that bridges activated factor (F)IX and FX, mimicking the function of missing activated FVIII and thus...

Prevalence of JC Polyomavirus in Patients with Neuroinvasive Disease of Unknown Etiology in Croatia.

: John Cunningham polyomavirus (JCPyV) is a highly prevalent virus in the human population. The prevalence of JCPyV in patients with central nervous s...

Prognosis Forecast of Re-Irradiation for Recurrent Nasopharyngeal Carcinoma Based on Deep Learning Multi-Modal Information Fusion.

Radiation therapy is the primary treatment for recurrent nasopharyngeal carcinoma. However, it may induce necrosis of the nasopharynx, leading to seve...

EUS coil and glue for gastric varices-prevent, treat and rescue, one therapy to rule them all?

BACKGROUND AND OBJECTIVES: In portal hypertension, gastric varix-associated bleeding is known to have higher transfusion requirements, uncontrolled bl...

Correlation Between Statin Use and Symptomatic Venous Thromboembolism Incidence in Patients With Ankle Fracture: A Machine Learning Approach.

BACKGROUND: Identifying factors that correlate with the incidence of venous thromboembolism (VTE) has the potential to improve VTE prevention and posi...

Chewing gum prophylaxis for postoperative nausea and vomiting in the intensive care unit: a pilot randomised controlled trial.

To test the effectiveness of chewing gum in the prophylaxis of postoperative nausea and vomiting (PONV) in patients admitted to the intensive care un...

Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies.

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clin...