Differentiation of epilepsy and psychogenic nonepileptic events based on body fluid characteristics

Biobehavioral approach to distinguishing panic symptoms from medical illness

Panic disorder is a common psychiatric diagnosis characterized by acute, distressing somatic symptoms that mimic medically-relevant symptoms. As a result, individuals with panic disorder overutilize personal and healthcare resources in an attempt to diagnose and treat physical symptoms that are often medically benign. A biobehavioral perspective on these symptoms is needed that integrates psychological and medical knowledge to avoid costly treatments and prolonged suffering. This narrative review examines six common somatic symptoms of panic attacks (non-cardiac chest pain, palpitations, dyspnea, dizziness, abdominal distress, and paresthesia), identified in the literature as the most severe, prevalent, or critical for differential diagnosis in somatic illness, including long COVID. We review somatic illnesses that are commonly comorbid or produce panic-like symptoms, their relevant risk factors, characteristics that assist in distinguishing them from panic, and treatment approaches that are typical for these conditions. Additionally, this review discusses key factors, including cultural considerations, to assist healthcare professionals in differentiating benign from medically relevant symptoms in panic sufferers.

Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist

PURPOSE OF REVIEW

Machine Learning (ML) and Artificial Intelligence (AI) are data-driven techniques to translate raw data into applicable and interpretable insights that can assist in clinical decision making. Some of these tools have extremely promising initial results, earning both great excitement and creating hype. This non-technical article reviews recent developments in ML/AI in epilepsy to assist the current practicing epileptologist in understanding both the benefits and limitations of integrating ML/AI tools into their clinical practice.

RECENT FINDINGS

ML/AI tools have been developed to assist clinicians in almost every clinical decision including (1) predicting future epilepsy in people at risk, (2) detecting and monitoring for seizures, (3) differentiating epilepsy from mimics, (4) using data to improve neuroanatomic localization and lateralization, and (5) tracking and predicting response to medical and surgical treatments. We also discuss practical, ethical, and equity considerations in the development and application of ML/AI tools including chatbots based on Large Language Models (e.g., ChatGPT). ML/AI tools will change how clinical medicine is practiced, but, with rare exceptions, the transferability to other centers, effectiveness, and safety of these approaches have not yet been established rigorously. In the future, ML/AI will not replace epileptologists, but epileptologists with ML/AI will replace epileptologists without ML/AI.