69 research outputs found
Driver Distraction Identification with an Ensemble of Convolutional Neural Networks
The World Health Organization (WHO) reported 1.25 million deaths yearly due
to road traffic accidents worldwide and the number has been continuously
increasing over the last few years. Nearly fifth of these accidents are caused
by distracted drivers. Existing work of distracted driver detection is
concerned with a small set of distractions (mostly, cell phone usage).
Unreliable ad-hoc methods are often used.In this paper, we present the first
publicly available dataset for driver distraction identification with more
distraction postures than existing alternatives. In addition, we propose a
reliable deep learning-based solution that achieves a 90% accuracy. The system
consists of a genetically-weighted ensemble of convolutional neural networks,
we show that a weighted ensemble of classifiers using a genetic algorithm
yields in a better classification confidence. We also study the effect of
different visual elements in distraction detection by means of face and hand
localizations, and skin segmentation. Finally, we present a thinned version of
our ensemble that could achieve 84.64% classification accuracy and operate in a
real-time environment.Comment: arXiv admin note: substantial text overlap with arXiv:1706.0949
The design of a mobile platform providing personalized assistance to older multimorbid patients with mild dementia or mild cognitive impairment (MCI)
Management of multiple chronic conditions introduces demanding challenges for patients. This situation becomes more complex when multimorbidity is associated with dementia. In this paper, we present the design of a mobile Patient Empowerment Platform that enables older multimorbid patients with mild dementia or mild cognitive impairment (MCI) to easily follow their complex care plans and increase their adherence. We focus on the presentation of the human-centered design process that we have followed with the involvement of patients, informal caregivers, and healthcare professionals via the clinical pilot sites of the CAREPATH project. We elaborate the design challenges we have faced and present the iterative mock-ups that have been created in cooperation with end users to address these challenges and the final PEP design
Extracorporeal Membrane Oxygenation for Acute Pediatric Respiratory Failure
This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.The use of extracorporeal membrane oxygenation (ECMO) to support children with acute respiratory failure has steadily increased over the past several decades, with major advancements having been made in the care of these children. There are, however, many controversies regarding indications for initiating ECMO in this setting and the appropriate management strategies thereafter. Broad indications for ECMO include hypoxia, hypercarbia, and severe air leak syndrome, with hypoxia being the most common. There are many disease-specific considerations when evaluating children for ECMO, but there are currently very few, if any, absolute contraindications. Venovenous rather than veno-arterial ECMO cannulation is the preferred configuration for ECMO support of acute respiratory failure due to its superior side-effect profile. The approach to lung management on ECMO is variable and should be individualized to the patient, with the main goal of reducing the risk of VILI. ECMO is a relatively rare intervention, and there are likely a minimum number of cases per year at a given center to maintain competency. Patients who have prolonged ECMO runs (i.e., greater than 21 days) are less likely to survive, though no absolute duration of ECMO that would mandate withdrawal of ECMO support can be currently recommended
Protocol for creating a single, holistic and digitally implementable consensus clinical guideline for multiple multi-morbid conditions
Delivery of future healthcare information systems requires systems to support patients with multi-morbidity. Current approaches to computer interoperable guidelines typically consider only a single clinical guideline for a single condition. There is a need to establish a robust protocolized approach to the development of holistic consensus computer interoperable guidelines in the context of multi-morbidity. The presence of mild cognitive impairment (MCI) and dementia adds an additional challenge to the delivery of effective digital health solutions. CAREPATH proposes an ICT-based solution for the optimization of clinical practice in the treatment and management of multi-morbid older adults with mild cognitive impairment or mild dementia. In this manuscript, we present an evidence-based protocol for the development of a single computer interoperable holistic guideline for a collection of multi-morbid conditions. To the best of our knowledge, this is the first published protocol for the production of a consensus interoperable clinical guideline for people with multi-morbidity, with special focus on older adults with MCI or mild dementia. This addresses a still unmet need for such processes which are expected to play a central role for future integrated healthcare information systems
Correction to: Two years later: Is the SARS-CoV-2 pandemic still having an impact on emergency surgery? An international cross-sectional survey among WSES members
Background: The SARS-CoV-2 pandemic is still ongoing and a major challenge for health care services worldwide. In the first WSES COVID-19 emergency surgery survey, a strong negative impact on emergency surgery (ES) had been described already early in the pandemic situation. However, the knowledge is limited about current effects of the pandemic on patient flow through emergency rooms, daily routine and decision making in ES as well as their changes over time during the last two pandemic years. This second WSES COVID-19 emergency surgery survey investigates the impact of the SARS-CoV-2 pandemic on ES during the course of the pandemic.
Methods: A web survey had been distributed to medical specialists in ES during a four-week period from January 2022, investigating the impact of the pandemic on patients and septic diseases both requiring ES, structural problems due to the pandemic and time-to-intervention in ES routine.
Results: 367 collaborators from 59 countries responded to the survey. The majority indicated that the pandemic still significantly impacts on treatment and outcome of surgical emergency patients (83.1% and 78.5%, respectively). As reasons, the collaborators reported decreased case load in ES (44.7%), but patients presenting with more prolonged and severe diseases, especially concerning perforated appendicitis (62.1%) and diverticulitis (57.5%). Otherwise, approximately 50% of the participants still observe a delay in time-to-intervention in ES compared with the situation before the pandemic. Relevant causes leading to enlarged time-to-intervention in ES during the pandemic are persistent problems with in-hospital logistics, lacks in medical staff as well as operating room and intensive care capacities during the pandemic. This leads not only to the need for triage or transferring of ES patients to other hospitals, reported by 64.0% and 48.8% of the collaborators, respectively, but also to paradigm shifts in treatment modalities to non-operative approaches reported by 67.3% of the participants, especially in uncomplicated appendicitis, cholecystitis and multiple-recurrent diverticulitis.
Conclusions: The SARS-CoV-2 pandemic still significantly impacts on care and outcome of patients in ES. Well-known problems with in-hospital logistics are not sufficiently resolved by now; however, medical staff shortages and reduced capacities have been dramatically aggravated over last two pandemic years
- …