Methods: Relevant peer-reviewed articles were identified by means of a systematic review. The literature was searched from 20 May 2020 to 20 June 2020. The search included the databases PubMed, Scopus and Web of Science (2010 - April 2020). A total of 4,139 papers related to rare diseases were identified; with 1,205 papers obtained from Scopus; 2,476 papers from PubMed; and 458 from Web of Science with keyword search "ethics" AND "rare" AND "disease", "ethical" AND "orphan", "ethical" AND "orphan" AND "drug", and "ethical" AND "rare" AND "disease". Finally, XX studies were chosen for further analysis.
Results: The main findings reveal five main ethical issues. The most essential one shows that funding research and development in the field of orphan drugs poses an almost impossible dilemma. Other issues include the significance of non-economic values like compassion and beneficence in decision-making related to orphan drugs and rare diseases; the identification of limits to labelling diseases as rare; barriers to global, supranational and international cooperation; and last but not least, determining and establishing panels of decision-makers.
Conclusions: A strictly global approach would be the most appropriate way to deal with rare diseases. Nonetheless, international, let alone global, cooperation seems to be completely beyond the reach of the current international community, although the EU, for instance, has a centralized procedure for labelling orphan drugs. This deficit in international cooperation can be partly explained by the fact that the current technologically globalized world still lacks globally accepted ethical values and rules. This is further aggravated by unresolved international and intercultural conflicts. In addition, the sub-interests of various parties as well as the lack of desire to deal with other people's problems need to be taken into account. The aforementioned problems are difficult to avoid. Nevertheless, let us be cautiously optimistic. At least, there are people who raise ethical questions about rare diseases and orphan drugs.
METHODS: The methodology is built-in deep data analysis for normalization. In comparison to previous research, the system does not necessitate a feature extraction process that optimizes and reduces system complexity. The data classification is provided by a designed 8-layer deep convolutional neural network.
RESULTS: Depending on used data, we have achieved the accuracy, specificity, and sensitivity of 98%, 98%, and 98.5% on the short-term Bonn EEG dataset, and 96.99%, 96.89%, and 97.06% on the long-term CHB-MIT EEG dataset.
CONCLUSIONS: Through the approach to detection, the system offers an optimized solution for seizure diagnosis health problems. The proposed solution should be implemented in all clinical or home environments for decision support.
RESULTS: The most significant result is the differences between image qualities of the thermograms captured by thermal camera models. In other words, the image quality of the thermal images in FLIR One is higher than SEEK Compact PRO. However, the thermal images of FLIR One are noisier than SEEK Compact PRO since the thermal resolution of FLIR One is 160 × 120 while it is 320 × 240 in SEEK Compact PRO.
CONCLUSION: Detecting and revealing the inhomogeneous temperature distribution on the injured toe of the subject, we, in this paper, analyzed the imaging results of two different smartphone-based thermal camera models by making comparison among various thermograms. Utilizing the feasibility of the proposed method for faster and comparative diagnosis in biomedical problems is the main contribution of this study.