Peer-support interventions can **reduce depression and fatigue in people with multiple sclerosis (MS)** by providing emotional connection, shared understanding, and practical coping strategies. These interventions create a space where individuals with MS can relate to others facing similar challenges, which…
Caregiver burden and mental health play significant roles in the outcomes of patients with Multiple Sclerosis (MS). MS is a chronic and often disabling disease that affects the central nervous system, leading to a wide range of physical, cognitive, and…
The economic impact of early high-efficacy therapy compared to a step-up approach in multiple sclerosis (MS) is significant and multifaceted, affecting both direct healthcare costs and broader societal expenses. Early high-efficacy therapy involves initiating potent disease-modifying treatments soon after diagnosis,…
Cognitive rehabilitation has emerged as a promising approach to help preserve work capacity in people with multiple sclerosis (MS), a chronic neurological condition often accompanied by cognitive impairments that can affect daily functioning and employment. MS can cause difficulties in…
Workplace accommodations play a crucial role in supporting individuals with Multiple Sclerosis (MS) to maintain long-term employment. MS is a chronic neurological condition that can cause a wide range of symptoms, including fatigue, mobility challenges, cognitive difficulties, and fluctuating physical…
Federated learning offers a promising approach to **protecting privacy while advancing multiple sclerosis (MS) research** by enabling collaborative data analysis without sharing sensitive patient information. This method allows multiple healthcare institutions to jointly train machine learning models on their local…
AI models forecast relapse risk from multimodal data streams by integrating and analyzing diverse types of information—such as physiological signals, behavioral patterns, speech, text, and social interactions—to detect subtle changes that precede a relapse. These models use advanced machine learning…
Digital twins have emerged as a groundbreaking technology in healthcare, offering the potential to simulate and predict individualized treatment responses for complex diseases like multiple sclerosis (MS). At their core, digital twins are highly detailed, computer-generated models that replicate the…
Patient-reported outcomes have become a crucial tool in capturing the invisible symptoms of multiple sclerosis (MS), a chronic and often debilitating neurological condition. MS is characterized by a wide range of symptoms, many of which are not immediately visible to…
When considering pragmatic trial designs for rapidly evolving multiple sclerosis (MS) therapeutics, the key challenge is to balance scientific rigor with real-world applicability and flexibility. MS is a complex, heterogeneous disease with multiple subtypes and variable progression rates, and new…