Forward-Forward Training of an Optical Neural Network

Neural networks (NN) have demonstrated remarkable capabilities in various tasks, but their computation-intensive nature demands faster and more energy-efficient hardware implementations. Optics-based platforms, using technologies such as silicon photonics and spatial light modulators, offer promising avenues for achieving this goal. However, training multiple trainable layers in tandem with these physical systems poses challenges, as they are difficult to fully characterize and describe with differentiable functions, hindering the use of error backpropagation algorithm. The recently introduced Forward-Forward Algorithm (FFA) eliminates the need for perfect characterization of the learning system and shows promise for efficient training with large numbers of programmable parameters. The FFA does not require backpropagating an error signal to update the weights, rather the weights are updated by only sending information in one direction. The local loss function for each set of trainable weights enables low-power analog hardware implementations without resorting to metaheuristic algorithms or reinforcement learning. In this paper, we present an experiment utilizing multimode nonlinear wave propagation in an optical fiber demonstrating the feasibility of the FFA approach using an optical system. The results show that incorporating optical transforms in multilayer NN architectures trained with the FFA, can lead to performance improvements, even with a relatively small number of trainable weights. The proposed method offers a new path to the challenge of training optical NNs and provides insights into leveraging physical transformations for enhancing NN performance

Detection of SARS-associated Coronavirus in Throat Wash and Saliva in Early Diagnosis

Early detection of SARS-CoV in throat wash and saliva suggests that these specimens are ideal for SARS diagnosis

Risk factors for fatal candidemia caused by Candida albicans and non-albicans Candida species

BACKGROUND: Invasive fungal infections, such as candidemia, caused by Candida species have been increasing. Candidemia is not only associated with a high mortality (30% to 40%) but also extends the length of hospital stay and increases the costs of medical care. Sepsis caused by Candida species is clinically indistinguishable from bacterial infections. Although, the clinical presentations of the patients with candidemia caused by Candida albicans and non-albicans Candida species (NAC) are indistinguishable, the susceptibilities to antifungal agents of these species are different. In this study, we attempted to identify the risk factors for candidemia caused by C. albicans and NAC in the hope that this may guide initial empiric therapy. METHODS: A retrospective chart review was conducted during 1996 to 1999 at the Veterans General Hospital-Taipei. RESULTS: There were 130 fatal cases of candidemia, including 68 patients with C. albicans and 62 with NAC. Candidemia was the most likely cause of death in 55 of the 130 patients (42.3 %). There was no significant difference in the distribution of Candida species between those died of candidemia and those died of underlying conditions. Patients who had one of the following conditions were more likely to have C. albicans, age ≧ 65 years, immunosuppression accounted to prior use of steroids, leukocytosis, in the intensive care unit (ICU), and intravascular and urinary catheters. Patients who had undergone cancer chemotherapy often appeared less critically ill and were more likely to have NAC. CONCLUSION: Clinical and epidemiological differences in the risk factors between candidemia caused by C. albicans and NAC may provide helpful clues to initiate empiric therapy for patients infected with C. albicans versus NAC

DISCOVERING DISASTER EVENTS FROM SOCIAL MEDIA STREAMS

Natural and man-made disasters can both cause severe loss of lives and economic damages. Examples include earthquakes, floods, and road crashes. Nevertheless, to rapidly and accurately identify the latest status of a disaster event is undoubtedly one of the most difficult tasks for agencies in crisis management. In this work, we thus propose to monitor online data streams in social media for detecting and tracking real world events. Unlike conventional media, social media is advantageous because of its immediateness, huge data scale, and worldwide availability. Nevertheless, the messages generated by netizens could be incomplete, subjective, or even error prone. Only with an appropriately designated scheme, invaluable clues embedded in huge amounts of online messages can be discovered when carefully exploiting the information over content, temporal, and social dimensions. Specifically, we collect data from multiple social networks, conduct real-time analysis, and present interactive visualization. Experimental studies show that the proposed scheme is demonstrated to be feasible for agencies in practice

Programming the scalable optical learning operator with spatial-spectral optimization

Electronic computers have evolved drastically over the past years with an ever-growing demand for improved performance. However, the transfer of information from memory and high energy consumption have emerged as issues that require solutions. Optical techniques are considered promising solutions to these problems with higher speed than their electronic counterparts and with reduced energy consumption. Here, we use the optical reservoir computing framework we have previously described (Scalable Optical Learning Operator or SOLO) to program the spatial-spectral output of the light after nonlinear propagation in a multimode fiber. The novelty in the current paper is that the system is programmed through an output sampling scheme, similar to that used in hyperspectral imaging in astronomy. Linear and nonlinear computations are performed by light in the multimode fiber and the high dimensional spatial-spectral information at the fiber output is optically programmed before it reaches the camera. We then used a digital computer to classify the programmed output of the multi-mode fiber using a simple, single layer network. When combining front-end programming and the proposed spatial-spectral programming, we were able to achieve 89.9% classification accuracy on the dataset consisting of chest X-ray images from COVID-19 patients. At the same time, we obtained a decrease of 99% in the number of tunable parameters compared to an equivalently performing digital neural network. These results show that the performance of programmed SOLO is comparable with cutting-edge electronic computing platforms, albeit with a much-reduced number of electronic operations

Dengue Fever Scoring System: New Strategy for the Early Detection of Acute Dengue Virus Infection in Taiwan

Dengue fever is an important public health problem in Southern Taiwan. The purpose of this study was to develop a dengue scoring system using a three-stage process, which may be used as a guidance tool for the early diagnosis of dengue fever. Methods: A retrospective study was conducted to identify factors useful for the early diagnosis of dengue fever. We assessed the clinical and laboratory features of 89 adult patients with dengue from 2002 to 2004 at a community-based hospital. They were compared with 14 patients with scrub typhus, 104 with Q fever, and 35 with murine typhus, which might present similar symptoms and signs as dengue infection. A scoring system was designed after analysis of the retrospective study and with the assistance of 10 expert clinicians. For the second stage, we evaluated efficiency in differentiating dengue fever from Q fever, scrub typhus and murine typhus in three hospitals from 2002 to 2005. For the third stage, we prospectively used the dengue scoring system for 498 cases that clinically were suspected as having dengue infection in the city of Kaohsiung from January 2006 to September 2006. Results: The performance of the scoring system was 88.1% sensitivity, 94.9% specificity, 95.7% positive predictive value (PPV), and 86.1% negative predictive value (NPV). Evaluation of the scoring system at the third stage revealed 90.7% sensitivity, 86.9% specificity, 81.4% PPV, and 93.6% NPV. Conclusion: The dengue scoring system had a high NPV that might be helpful in the early diagnosis of dengue fever in adults before laboratory data are available

Risk factors for fatal candidemia caused by <it>Candida albicans </it>and non-albicans <it>Candida </it>species

Abstract Background Invasive fungal infections, such as candidemia, caused by Candida species have been increasing. Candidemia is not only associated with a high mortality (30% to 40%) but also extends the length of hospital stay and increases the costs of medical care. Sepsis caused by Candida species is clinically indistinguishable from bacterial infections. Although, the clinical presentations of the patients with candidemia caused by Candida albicans and non-albicans Candida species (NAC) are indistinguishable, the susceptibilities to antifungal agents of these species are different. In this study, we attempted to identify the risk factors for candidemia caused by C. albicans and NAC in the hope that this may guide initial empiric therapy. Methods A retrospective chart review was conducted during 1996 to 1999 at the Veterans General Hospital-Taipei. Results There were 130 fatal cases of candidemia, including 68 patients with C. albicans and 62 with NAC. Candidemia was the most likely cause of death in 55 of the 130 patients (42.3 %). There was no significant difference in the distribution of Candida species between those died of candidemia and those died of underlying conditions. Patients who had one of the following conditions were more likely to have C. albicans, age ≧ 65 years, immunosuppression accounted to prior use of steroids, leukocytosis, in the intensive care unit (ICU), and intravascular and urinary catheters. Patients who had undergone cancer chemotherapy often appeared less critically ill and were more likely to have NAC. Conclusion Clinical and epidemiological differences in the risk factors between candidemia caused by C. albicans and NAC may provide helpful clues to initiate empiric therapy for patients infected with C. albicans versus NAC.</p

Workplace interpersonal conflicts among the healthcare workers: Retrospective exploration from the institutional incident reporting system of a university-affiliated medical center

<div><p>Objective</p><p>There have been concerns about the workplace interpersonal conflict (WIC) among healthcare workers. As healthcare organizations have applied the incident reporting system (IRS) widely for safety-related incidents, we proposed that this system might provide a channel to explore the WICs.</p><p>Methods</p><p>We retrospectively reviewed the reports to the IRS from July 2010 to June 2013 in a medical center. We identified the WICs and typed these conflicts according to the two foci (task content/process and interpersonal relationship) and the three properties (disagreement, interference, and negative emotion), and analyzed relevant data.</p><p>Results</p><p>Of the 147 incidents with WIC, the most common related processes were patient transfer (20%), laboratory tests (17%), surgery (16%) and medical imaging (16%). All of the 147 incidents with WIC focused on task content or task process, but 41 (27.9%) also focused on the interpersonal relationship. We found disagreement, interference, and negative emotion in 91.2%, 88.4%, and 55.8% of the cases, respectively. Nurses (57%) were most often the reporting workers, while the most common encounter was the nurse-doctor interaction (33%), and the majority (67%) of the conflicts were experienced concurrently with the incidents. There was a significant difference in the distribution of worker job types between cases focused on the interpersonal relationship and those without (p = 0.0064). The doctors were more frequently as the reporter when the conflicts focused on the interpersonal relationship (34.1%) than not on it (17.0%). The distributions of worker job types were similar between those with and without negative emotion (p = 0.125).</p><p>Conclusions</p><p>The institutional IRS is a useful place to report the workplace interpersonal conflicts actively. The healthcare systems need to improve the channels to communicate, manage and resolve these conflicts.</p></div

Personnel involved and interpersonal relationship.

<p>Personnel involved and interpersonal relationship.</p