Classification panel

As in Europe, the classification of devices plays a central role in the regulation of devices in the US. However, there are a number of differences compared to the European approach. First of all, responsibility for classification rests with the FDA rather than with the manufacturers. When the regulations were introduced, the FDA mandated expert advisory panels (classification panels) to consider the different types of device that existed on the market at that time. The FDA provided classification questionnaires to act as guidelines for the panels when assessing the devices. In determining the safety and effectiveness of a device for purposes of classification, the classification panels had to consider the intended user (not part of EU criteria), the... 

There is a huge variety of medical devices. The range and depth of medical devices (and medical textiles) can be appreciated from Table 12.1, where the FDA classificafimi of medical devices into speciality Device Classification Panels such as Cardiovascular... 

FDA Device Classification Panels, 2014. FDA Device Classification Panels [OnUne]. Available http //www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/Overview/... 

When a block is inside, the entrance panel is closed and the inspection is ready to start. The inside of the stainless steel X-ray tubehead housing is clad in lead with an on/ofT shutter in front of a thin plastic X-ray window. The thin window is to ensure the IP 65 classification. The window is of plastic that is not affected by the cleaning agents. The on/off shutter is interlocked with the entrance and exit panels so X-rays can be kept on at all times without risk of radiation leakage or exposure of the frozen fish blocks prior to the actual inspection. 

Classification Type pce Panel spalling loss, max. Cold modulus of Other test requirements... 

Plywood is also divided into softwood and hardwood plywood products. The classification depends on the type of wood the face pHes are made from. The principal appHcation for 1 cm and thicker hardwood plywoods are cabinets and furniture. The thinner grades are used to make paneling and doorskins, which represent approximately 56% of the total hardwood plywood products. The total market in 1989 was estimated to be 2.1 biUion. 

Originally the classification of materials was derived from tests of proprietary explosion-proof (flameproof) enclosures. There were no published criteria. Equipment was approved relative to the lowest ignition temperature of any material in the group (Magison 1987). In about 1965 the U.S. Coast Guard asked the National Academy of Sciences (NAS) to form a panel to classify 200 materials of commerce. The Electrical Hazards Panel of the Committee on Hazardous Materials was formed by the NAS. The Panel studied many ways to estimate the hazard classification of materials. The Panel finally reported to die U.S. Coast Guard in 1970 that no workable, predicdve scheme could be defined, and it then proceeded to assign tentative classifications to the 200 materials. 

The classification structure for PIFs used in this chapter is based on the model of human error as arising from a mismatch between demands and resources which was described in Chapter 1, Section 1.6 (Figure 1.6). In this model demands were seen as requirements for human performance which arise from the characteristics of the process environment (e.g., the need to monitor a panel or to be able to fix a seal in a flange) and the nature of the human capabilities to satisfy these demands (e.g., skills of perception, thinking, and physical action). These demands are met by the individual and group resources of personnel and the extent to which the design of the task allows these resources to be effectively deployed. Where demands exceeded resources, errors could be expected to occur. 

Error probabilities that are used in decomposition approaches are all derived in basically the same manner. Some explicit or implicit form of task classification is used to derive categories of tasks in the domain addressed by the technique. For example, typical THERP categories are selections of switches from control panels, walk-around inspections, responding to alarms and operating valves. 

The National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) recommends that a fasting lipoprotein profile and risk factor assessment be used in the initial classification of adults. 

FIGURE 5.16 Full classification tree for the data example in Figure 5.15 in the left panel, and the resulting classification lines in the right panel. The dashed lines will not be used when the tree is pruned to its optimal complexity. 

It can however be used in a standardized profiling panel calibrated against known promiscuous compounds. The THR classification given above is used in the Novartis in vitro safety pharmacology profiling panel where >50 targets have been tested. 

Chen et al. (2008) employed a commercial electronic tongue, based on an array of seven sensors, to classify 80 green tea samples on the basis of their taste grade, which is usually assessed by a panel test. PCA was employed as an explorative tool, while fc-NN and a back propagation artificial neural network (BP-ANN) were used for supervised classification. Both the techniques provide excellent results, achieving 100% prediction ability on a test set composed of 40 samples (one-half of the total number). In cases like this, when a simple technique, such as fc-NN, is able to supply excellent outcomes, the utilization of a complex technique, like BP-ANN, does not appear justified from a practical point of view. 

It is the goal of array-based prognostics to utilize a panel of markers that are more accurately able to stratify patients into prognostic groupings. There are several examples in the literature of biomarker panels identified by microarray analysis that may have some relation to prognostic outcome (4, 77, 78, 79,80). However, the issue remains that many of these biomarker panels do not afford sufficient specificity or sensitivity to warrant clinical application. Microarrays offer the potential to profile tumors at a finer level of detail than what can be obtained by the pathologist however, it is the reliance on classification from traditional pathology that has confounded many studies. 

For the third classification, known as slow burning , the exposure is 20 minutes following the standard time-temperature curve (3). No flame from the specimen may reach the angle frame at any point, and all flaming must cease within 5 minutes after the test flame is discontinued. If a material fails to meet these test requirements, it is rated as combustible. For all classifications, there are restrictions as to the amount of material which may fall from the test panel during the exposure period. 

The device class classification under Section 513 of the Act and the appropriate panel (if known) should be submitted. Justification should be provided for devices not classified. 

C16. Chen, C. C., Raikow, R. B., Sonmez-Alpan, E., and Swerdlow, S. H., Classification of small B-cell lymphoid neoplasms using a paraffin section immunohistochemical panel. Appl. Immuno-histochem. Mol. Morphol. 8, 1-11 (2000). 

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