4 research outputs found
Management of missed injuries in polytrauma patient
State University of Medicine and Pharmacy āNicolae TestemiČanuā, Republic of Moldova, Institute of Emergency Medicine, ChiČinÄu, Republic of Moldova, Al VIII-lea Congres NaÅ£ional de Ortopedie Či Traumatologie cu participare internaÅ£ionalÄ 12-14 octombrie 2016According CRICO Strategies, among the most common and costly medical errors committed in emergency departments are
establishing a delay in diagnosis or misdiagnosis, which can have a tragic end for the patient.
The management of multiple trauma patients presents a worldwide diagnostic and therapeutic challenge to trauma,
orthopedic and general surgeons. Significant injuries can be missed during primary and secondary surveys in multiply
injured patients, for whom resuscitation, diagnosis and therapy have to proceed simultaneously. Many factors involved in
the initial resuscitation of the multiple trauma patients, such as altered level of consciousness, hemodynamic instability, or
inexperience and inadequate diagnostic evaluation, may lead to missed injuries or a āmedical errorsā. The injuries can be
missed at any stage of the management of the trauma patient, including intraoperatively, and may involve all regions of the
body.
Management of polytraumatised patient need application of primary and secondary survey protocols, as is the ATLS
(Advanced Trauma Life Support) protocol, will minimize the chance of life-threatening critical medical errors.
Also, intraoperative careful approach is needed for all patients, but especially for hemodynamically unstable patients, giving
priority to other regions of the human body than appreciated as trauma, for the presence of vascular lesions.
Examination of polytraumatised patient with special vigilance in a tertiary look, after patient returns to consciousness, will
help detect missed lesions during the initial assessment. In most cases we detect missed lesions. This approach will lead to
early detection of missed injuries and reduce lost their consequences
A spiking recurrent neural network with phase change memory neurons and synapses for the accelerated solution of constraint satisfaction problems
Pedretti G, Mannocci P, Hashemkhani S, et al. A spiking recurrent neural network with phase change memory neurons and synapses for the accelerated solution of constraint satisfaction problems. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 2020;6(1):189-97.Data-intensive computing applications, such as object recognition, time series prediction, and optimization tasks, are becoming increasingly important in several fields, including smart mobility, health, and industry. Because of the large amount of data involved in the computation, the conventional von Neumann architecture suffers from excessive latency and energy consumption due to the memory bottleneck. A more efficient approach consists of in-memory computing (IMC), where computational operations are directly carried out within the data. IMC can take advantage of the rich physics of memory devices, such as their ability to store analog values to be used in matrix-vector multiplication (MVM) and their stochasticity that is highly valuable in the frame of optimization and constraint satisfaction problems (CSPs). This article presents a stochastic spiking neuron based on a phase-change memory (PCM) device for the solution of CSPs within a Hopfield recurrent neural network (RNN). In the RNN, the PCM cell is used as the integrating element of a stochastic neuron, supporting the solution of a typical CSP, namely a Sudoku puzzle in hardware. Finally, the ability to solve Sudoku puzzles using RNNs with PCM-based neurons is studied for increasing size of Sudoku puzzles by a compact simulation model, thus supporting our PCM-based RNN for data-intensive computing
A Spiking Recurrent Neural Network with Phase Change Memory Synapses for Decision Making
Pedretti G, Milo V, Hashemkhani S, et al. A Spiking Recurrent Neural Network with Phase Change Memory Synapses for Decision Making. Presented at the 2020 IEEE International Symposium on Circuits & Systems, Seville, Spain