ABSTRACT
Essential tremors (ETs) commonly manifest as involuntary shaking of the hands that disrupt daily activities. These tremors involve the central motor network of the cerebellum, thalamus, and cortical networks, leading to different clinical phenotypes. The goal of this review was to establish evidence-based recommendations for effective care and simplify decisions for those dealing with ET. For this narrative literature review, we conducted a thorough search using core keywords such as "essential tremor" and "therapy." From the 27 selected articles, relevant data were presented regarding pathophysiology, medications, and other treatment options, with necessary supplemental data such as side effects and use cases. This paper examines treatments for ET, including commonly prescribed medications such as propranolol and primidone; invasive treatments such as deep brain stimulation, focused ultrasound thalamotomy, transcranial magnetic stimulation, and some surgical methods; and non-invasive methods such as the neuromodulation technique of transcutaneous afferent patterned stimulation. Overall, this study presents a synthesized understanding of the currently available modalities for managing ETs. It is intended to guide care providers in choosing the best possible method to contain symptoms.
ABSTRACT
Radiology has been a pioneer in the healthcare industry's digital transformation, incorporating digital imaging systems like picture archiving and communication system (PACS) and teleradiology over the past thirty years. This shift has reshaped radiology services, positioning the field at a crucial junction for potential evolution into an integrated diagnostic service through artificial intelligence and machine learning. These technologies offer advanced tools for radiology's transformation. The radiology community has advanced computer-aided diagnosis (CAD) tools using machine learning techniques, notably deep learning convolutional neural networks (CNNs), for medical image pattern recognition. However, the integration of CAD tools into clinical practice has been hindered by challenges in workflow integration, unclear business models, and limited clinical benefits, despite development dating back to the 1990s. This comprehensive review focuses on detecting chest-related diseases through techniques like chest X-rays (CXRs), magnetic resonance imaging (MRI), nuclear medicine, and computed tomography (CT) scans. It examines the utilization of computer-aided programs by researchers for disease detection, addressing key areas: the role of computer-aided programs in disease detection advancement, recent developments in MRI, CXR, radioactive tracers, and CT scans for chest disease identification, research gaps for more effective development, and the incorporation of machine learning programs into diagnostic tools.
