Pain Management

Spatiotemporal-decoupled interactive learning for traffic flow prediction.

Accurate traffic flow prediction is a core capability of intelligent transportation systems, supporting trip planning, network dispatch, and management decisions. Most existing approaches overlook interactive learning of spatiotemporal dependencies and struggle to accommodate pattern diversity arising from spatial heterogeneity and multi-scale temporal variation. To address these limitations, this...

Prevalence and factors associated with suicidal ideation based on the Malaysia National Health and Morbidity Survey: A machine learning analysis.

BACKGROUND: This study estimated the prevalence of past-two-week suicidal ideation and examined its demographic, clinical, and health-related correlates in a nationally representative Malaysian sample using machine learning. METHODS: The National Health and Morbidity Survey (NHMS) 2019 in Malaysia comprised a nationally representative sample of 11,674 adults aged 18 and above. Suicidal ideation wa...

Decoding lactylation in neuropathic pain: Immune cell infiltration patterns and machine learning-identified candidate biomarkers.

This study aimed to identify lactylation-associated genes linked to immune infiltration and diagnostic potential in neuropathic pain using integrated ...

Identifying the 'gray zone': Developing scalable methods to detect opioid misuse in veterans on long-term opioid therapy for pain.

BACKGROUND: Patients prescribed opioids who are at high risk for misuse but don't meet diagnostic criteria for opioid use disorder (OUD) fall into a c...

Brain Mechanisms of Pain Anticipation in Chronic Low Back Pain: Insights into Phenotypical Responses to Mind-Body Therapy.

Pain perception and emotional processing share common predictive mechanisms influenced by anticipation, expectation, and uncertainty. This study ident...

Thalamocortical and corticostriatal pathways in the progression from acute to chronic musculoskeletal pain: an fMRI study.

Most people experience acute pain as a temporary condition, while a small subset develops chronic pain. The role of pain-related circuits driving this...

Artificial intelligence and predictive analytics in obstetric anesthesia: early warning for maternal complications.

PURPOSE OF REVIEW: Maternal morbidity and mortality remain largely preventable, yet current risk-assessment tools identify only a fraction of women wh...

From Observation to Prediction: Machine Learning Analysis of Progression of Visual loss in Nonarteritic Anterior Ischemic Optic Neuropathy.

OBJECTIVE: To determine whether combinations of modifiable clinical/systemic risk factors and structured trial variables predict early disease progres...

Size doesn't matter: Assessing the trustworthiness of large language models in medical contexts: A focus on epidural information retrieval.

BACKGROUND: Since the release of ChatGPT, numerous LLMs have emerged, providing easy access to information without the need for technical expertise. H...

Postmarketing Safety of Transcranial Magnetic Stimulation: A 10-Year MAUDE Database Analysis of Adverse Events and Technological Advancements.

Background: Transcranial magnetic stimulation (TMS) is an FDA-cleared neuromodulation technique with expanding clinical applications beyond major depr...

Disrupted and reorganized connectivity of brain networks in multiple sclerosis: a systematic review and meta-analysis of resting-state functional MRI.

BACKGROUND: Abnormalities in large-scale brain functional networks are implicated in multiple sclerosis (MS) and linked to clinical impairments, but r...

NeuroCLIP: A Multimodal Contrastive Learning Method for rTMS-treated Methamphetamine Addiction Analysis.

Methamphetamine dependence poses a significant global health challenge, yet its assessment and the evaluation of treatments like repetitive transcrani...

Computerized Self-Reported Medical History Taking to Support Early Rule Out of Major Adverse Cardiac Events in Patients With Acute Chest Pain: Post Hoc Analysis of the CLEOS-CPDS Prospective Cohort Study.

BACKGROUND: Self-reported, computerized history taking (CHT) may enable efficient collection of medical histories for acute chest pain management. OBJ...

Deep Learning-Based Epileptic Seizure Detection from EEG Signals and PPG signals Using LSTM and CNN Models.

Epilepsy is a chronic neurological disorder characterized by recurrent and unpredictable seizures that significantly affect patients' health and quali...

A systems approach identifies MERTK as a therapeutic vulnerability in ZFTA-RELA-driven ependymomas.

Ependymomas (EPN) are rare central nervous system tumors that account for approximately 10% of intracranial tumors in children and 4% in adults. Despi...

De novo identification of potent ingredients for proteasome activation in MT101-5 using an AI-driven approach.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by the intracellular accumulation of α-synuclein (α-syn) protein within Lewy bo...

Network control dynamics and subjective reactivity in physiological responses to psychosocial stress.

The ability to endure psychosocial stressors is critical for mental and physical well-being. Clarifying mechanisms that differentiate high- from low-t...

Chronic Pain Management: From Ancient Healing Practices to Advanced Medical Innovation.

Chronic pain is one of the most prevalent global health issues, significantly impacting physical and psychological health and resulting in reduced qua...

Comprehensive 3D Optical Coherence Tomography Dataset for AMD and DME: Facilitating Deep-Learning-Based 3D Segmentation.

Age-related macular degeneration (AMD) and diabetic macular edema (DME) are vision-threatening pathologies for which optical coherence tomography (OCT...

The use of the odds ratio product and self-reported data to detect comorbid insomnia and sleep apnea.

STUDY OBJECTIVES: To evaluate the utility of the odds ratio product (ORP) in differentiating comorbid insomnia and sleep apnea (COMISA) from obstructi...