Background Each rare disease only affects a small number of population. However, a total of 7000 rare diseases may affect 10% of the population. Due to the severity and lack of rare disease awareness, rare disease represents a huge challenge for the healthcare system. In Western countries, patient organizations have been playing an integral role in raising awareness, advocating legislation, and supporting drug development. This study aims to assess the unmet needs of rare disease patient organizations in China, and identify their unmet needs, providing essential information for the government and legislators. Results A total of 28 individuals representing 28 patient organizations in China were interviewed. Most organizations do not have official registration, employees, written standard operation protocol, or reliable financial resources. Misdiagnosis or delayed diagnosis is common, and treatment is often lacking. Due to the lack of financial resources, no organizations have been able to sponsor academic research, unlike their counterparts in Western countries. As to challenges, 71.4% of interviewees listed lack of rare disease awareness among the general public, while 67.9% selected lack of financial resources. Further, only 7.3% of these organizations received support from the government, and 28.6% received support from the general public. As to recommendations to the government, 82.1% of interviewees selected special insurance programs for rare diseases because rare diseases have been generally excluded from the national medical insurance programs. In addition, 78.6% of interviewees recommended to stimulate rare disease research, 75% recommended to import orphan drugs, and 71.4% recommended legislation of an orphan drug act, highlighting the urgent need of therapies. Conclusions Due to lack of support and rare disease awareness, patient organizations in China are still in the early phase. To empower these patient organizations, the interviewees’ recommendations, including legislating orphan drug act and releasing official definition of rare diseases, should be considered by the government and legislators.

Background It is estimated that there are over 16.8 million rare disease patients in China, representing a significant challenge for the healthcare system and society. Rare disease patients often experience delayed diagnosis, misdiagnosis, or improper treatment, which may be due to the lack of rare disease awareness among physicians. Materials and methods A total of 224 physicians from different hospitals in China participated in the questionnaire, and 9 rare disease experts were interviewed with open-ended questions. Results Most physicians (83.5%) were from Tertiary hospitals, which have over 500 beds. Only 5.3% of physicians were moderately or well aware of rare diseases. Most physicians (80.1%) had suspected their patients to have rare diseases less than 3 times. There was a strong support for special legislations for rare diseases and orphan drugs. Further, multinomial logistic regression (MLR) was used to determine whether hospitals, gender, and career length has an impact on perspectives and awareness. It was shown that male physicians were more likely to think newborn screening is important (p < 0.05). The longer the career length is, the more likely physicians believe that their previous education has not provided sufficient information about rare diseases and that their hospital has paid enough attention to rare diseases. Physicians from Tertiary A hospitals were more likely to rate the affordability of orphan drugs high. In addition, nine experts believed that rare disease awareness is essential for early diagnosis and timely treatment. These experts also made recommendations on how to improve rare disease awareness through medical school education and continuing training. Conclusions Our study highlighted the importance of improving rare disease awareness among physicians in China. Recommendations about how to improve rare disease awareness in medical school education and establish an online ‘information hub’ are made for considerations of policy-makers.

Artificial neural networks are powerful computational systems with interconnected neurons. Generally, these networks have a very large number of computation nodes which forces the designer to use software-based implementations. However, the software based implementations are offline and not suitable for portable or real-time applications. Experiments show that compared with the software based implementations, FPGA-based systems can greatly speed up the computation time, making them suitable for real-time situations and portable applications. However, the FPGA implementation of neural networks with a large number of nodes is still a challenging task. In this paper, we exploit stochastic bit streams in the Restricted Boltzmann Machine (RBM) to implement the classification of the RBM handwritten digit recognition application completely on an FPGA. We use finite state machinebased (FSM) stochastic circuits to implement the required sigmoid function and use the novel stochastic computing approach to perform all large matrix multiplications. Experimental results show that the proposed stochastic architecture has much more potential for tolerating faults while requiring much less hardware compared to the currently un-implementable deterministic binary approach when the RBM consists of a large number of neurons. Exploiting the features of stochastic circuits, our implementation achieves much better performance than a software-based approach.

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