Development of a Machine Learning Model for Predicting Weaning Outcomes Based Solely on Continuous Ventilator Parameters during Spontaneous Breathing Trials.

Discontinuing mechanical ventilation remains challenging. We developed a machine learning model to predict weaning outcomes using only continuous monitoring parameters obtained from ventilators during spontaneous breathing trials (SBTs). Patients who received mechanical ventilation in the medical intensive care unit at a tertiary university hospital from 2019-2021 were included in this study.

Association between choroid plexus volume and cognition in Parkinson disease.

Background And Purpose: The choroid plexus (CP) clears harmful metabolites from the central nervous system as part of the glymphatic system. We investigated the association of CP volume (CPV) with baseline and longitudinal cognitive decline in patients with Parkinson disease (PD).

Methods: We retrospectively reviewed the medical records of 240 patients with newly diagnosed PD who had undergone detailed neuropsychological tests and high-resolution T1-weighted structural magnetic resonance imaging during the initial assessment.

Association of choroid plexus volume with motor symptoms and dopaminergic degeneration in Parkinson's disease.

Background: The choroid plexus (CP) is involved in the clearance of harmful metabolites from the brain, as a part of the glymphatic system. This study aimed to investigate the association between CP volume (CPV), nigrostriatal dopaminergic degeneration and motor outcomes in Parkinson's disease (PD).

Methods: We retrospectively searched drug-naïve patients with early-stage PD who underwent dopamine transporter (DAT) scanning and MRI.

Immunoglobulin G4-Related Disease Involving Various Head and Neck Regions: A Case Report.

Immunoglobulin G4 (IgG4) related disease (IgG4-RD) is currently considered an immune-mediated condition and is recognized as a disorder group with common pathological, hematological, and clinical characteristics. This disease may involve diverse organs of the head and neck, and include mainly the lacrimal gland, orbit, thyroid gland, pituitary gland, and the meninges. Here, we report a case of IgG4-RD in a 65-year-old female showing head- and neck-limited but synchronously and mainly manifesting as otalgia and facial neuritis.

Serial changes of I-123 FP-CIT SPECT binding asymmetry in Parkinson's disease: Analysis of the PPMI data.

Background: Dopaminergic denervation and motor symptoms are usually asymmetric at the onset of Parkinson's disease (PD). In this study, we estimated the asymmetry of specific binding ratio (SBR) of I-123 FP-CIT SPECT images during 4-years of follow up, to demonstrate the pattern of serial changes of asymmetry.

Methods: Clinical and I-123 FP-CIT SPECT image data of 301 PD patients and 141 normal controls were reviewed from the Parkinson's Progression Markers Initiative cohort.

Factors associated with motor severity in vascular parkinsonism with normal dopamine transporter imaging.

Introduction: To delineate the determinants of motor severity in vascular parkinsonism (VaP), we investigated the impact of regional white matter intensity (WMH) burden and co-morbidities on the motor score in the patients with VaP and normal dopamine transporter (DAT) imaging.

Methods: In this multicenter, retrospective study, we reviewed the records of 63 patients diagnosed with VaP and normal DAT imaging on 18F-FP-CIT PET. Signal hyperintensities in deep white matter (DWMH), periventricular (PVH), basal ganglia (BG) regions, and infratentorial foci (ITF) were rated according to Scheltens scale, a semi-quantitative visual rating system.

Correlation of Dopaminergic Denervation and the Progression of Autonomic Dysfunctions in Different Clinical Subtypes of Parkinson's Disease.

Background: Autonomic dysfunctions occur in the early stage of Parkinson's disease (PD) and impact the quality of life during the progression of the disease. In this study, we evaluated the serial progression of autonomic dysfunctions between different subtypes of a prospective PD cohort.

Materials And Methods: From the Parkinson's Progression Markers Initiative (PPMI) database, 325 PD patients (age: 61.

Human-like Decision-Making System for Overtaking Stationary Vehicles Based on Traffic Scene Interpretation.

There are multifarious stationary vehicles in urban driving environments. Autonomous vehicles need to make appropriate overtaking maneuver decisions to navigate through the stationary vehicles. In literature, overtaking maneuver decision problems have been addressed in the perspective of either discretionary lane-change or parked vehicle classification.

Deep-Learning-Based Smartphone Application for Self-Diagnosis of Scleral Jaundice in Patients with Hepatobiliary and Pancreatic Diseases.

Outpatient detection of total bilirubin levels should be performed regularly to monitor the recurrence of jaundice in hepatobiliary and pancreatic disease patients. However, frequent hospital visits for blood testing are burdensome for patients with poor medical conditions. This study validates a novel deep-learning-based smartphone application for the self-diagnosis of scleral jaundice in such patients.

Vehicle Trajectory Prediction Using Hierarchical Graph Neural Network for Considering Interaction among Multimodal Maneuvers.

Predicting the trajectories of surrounding vehicles by considering their interactions is an essential ability for the functioning of autonomous vehicles. The subsequent movement of a vehicle is decided based on the multiple maneuvers of surrounding vehicles. Therefore, to predict the trajectories of surrounding vehicles, interactions among multiple maneuvers should be considered.

Irritable bowel syndrome and subsequent risk of Parkinson's disease: a nationwide population-based matched-cohort study.

Background: Gastrointestinal dysfunction (GI) is the most prevalent non-motor symptom of Parkinson's disease (PD), and its role in the risk of PD has been studied. In this study, we tried to evaluate whether irritable bowel syndrome (IBS) increased the risk of PD development stratified by sex, age, and IBS duration using a large nationwide cohort in Korea.

Methods: Patients aged ≥ 20 years with a primary diagnosis of IBS (ICD-10 codes: G56) more than three times were selected.

Limited Visibility Aware Motion Planning for Autonomous Valet Parking Using Reachable Set Estimation.

Autonomous driving helps drivers avoid paying attention to keeping to a lane or keeping a distance from the vehicle ahead. However, the autonomous driving is limited by the need to park upon the completion of driving. In this sense, automated valet parking (AVP) system is one of the promising technologies for enabling drivers to free themselves from the burden of parking.

Driver Characteristics Oriented Autonomous Longitudinal Driving System in Car-Following Situation.

Advanced driver assistance system such as adaptive cruise control, traffic jam assistance, and collision warning has been developed to reduce the driving burden and increase driving comfort in the car-following situation. These systems provide automated longitudinal driving to ensure safety and driving performance to satisfy unspecified individuals. However, drivers can feel a sense of heterogeneity when autonomous longitudinal control is performed by a general speed planning algorithm.

Semantic Point Cloud Mapping of LiDAR Based on Probabilistic Uncertainty Modeling for Autonomous Driving.

LiDAR-based Simultaneous Localization And Mapping (SLAM), which provides environmental information for autonomous vehicles by map building, is a major challenge for autonomous driving. In addition, the semantic information has been used for the LiDAR-based SLAM with the advent of deep neural network-based semantic segmentation algorithms. The semantic segmented point clouds provide a much greater range of functionality for autonomous vehicles than geometry alone, which can play an important role in the mapping step.

Inosine 5'-Monophosphate to Raise Serum Uric Acid Level in Multiple System Atrophy (IMPROVE-MSA study).

The aim of this trial was to investigate the safety, tolerability, and capability of serum uric acid (UA) elevation of inosine 5'-monophosphate (IMP) in multiple system atrophy (MSA). The IMPROVE-MSA trial was a randomized, double-blind, placebo-controlled trial in patients with MSA with no history of hyperuricemia-related disorders. The participants were assigned to placebo (n = 25) or IMP (n = 30) in a 1 to 1 ratio, and then followed up for 24 weeks.

Rapid drug increase and early onset of levodopa-induced dyskinesia in Parkinson's disease.

A higher levodopa dose is a strong risk factor for levodopa-induced dyskinesia (LID) in patients with Parkinson's disease (PD). However, levodopa dose can change during long-term medication. We explored the relationship between levodopa dose and time to onset of LID using longitudinal multicenter data.

Robust Parking Path Planning with Error-Adaptive Sampling under Perception Uncertainty.

In automated parking systems, a path planner generates a path to reach the vacant parking space detected by a perception system. To generate a safe parking path, accurate detection performance is required. However, the perception system always includes perception uncertainty, such as detection errors due to sensor noise and imperfect algorithms.

Areas of white matter hyperintensities and motor symptoms of Parkinson disease.

Objective: To determine whether deep white matter and periventricular hyperintensities affect the motor symptoms of Parkinson disease (PD) differently, we analyzed MRI and dopamine transporter imaging.

Methods: We analyzed the medical records of patients with de novo PD who underwent dopamine transporter PET scanning and MRI at their first visit. Deep white matter and periventricular hyperintensities were scored with a visual rating scale, and motor symptoms were assessed by Unified Parkinson's Disease Rating Scale motor score and tremor, rigidity, bradykinesia, and axial symptom subscores.

Prevalence and outcomes of young people with concurrent autism spectrum disorder and first episode of psychosis.

Background: The intersect and blurring of boundaries between schizophrenia spectrum disorders and autism spectrum disorder (ASD) has long been an area of confusion, in both nosology and clinical practice. Individuals with a comorbid presentation of the two spectra can present with a distinct phenomenological profile to those with psychosis or ASD alone.

Aims: To examine the prevalence rates of ASD in a cohort of young people presenting with a first episode of psychosis (FEP) and compare the demographic and clinical characteristics and functional outcomes between individuals with concurrent FEP and ASD, and individuals with FEP only.

Vehicle Deceleration Prediction Model to Reflect Individual Driver Characteristics by Online Parameter Learning for Autonomous Regenerative Braking of Electric Vehicles.

The connected powertrain control, which uses intelligent transportation system information, has been widely researched to improve driver convenience and energy efficiency. The vehicle state prediction on decelerating driving conditions can be applied to automatic regenerative braking in electric vehicles. However, drivers can feel a sense of heterogeneity when regenerative control is performed based on prediction results from a general prediction model.

Rapid Motion Segmentation of LiDAR Point Cloud Based on a Combination of Probabilistic and Evidential Approaches for Intelligent Vehicles.

Point clouds from light detecting and ranging (LiDAR) sensors represent increasingly important information for environmental object detection and classification of automated and intelligent vehicles. Objects in the driving environment can be classified as either d y n a m i c or s t a t i c depending on their movement characteristics. A LiDAR point cloud is also segmented into d y n a m i c and s t a t i c points based on the motion properties of the measured objects.

Deceleration Planning Algorithm Based on Classified Multi-Layer Perceptron Models for Smart Regenerative Braking of EV in Diverse Deceleration Conditions.

The smart regenerative braking system (SRS) is an autonomous version of one-pedal driving in electric vehicles. To implement SRS, a deceleration planning algorithm is necessary to generate the deceleration used in automatic regenerative control. To reduce the discomfort from the automatic regeneration, the deceleration should be similar to human driving.