Brevet USD432244 - Device for encasing an assay test strip

Numéro de publication	USD432244 S
Type de publication	Octroi
Numéro de demande	29/086,799
Date de publication	17 oct. 2000
Date de dépôt	20 avr. 1998
Inventeurs	Emory V. Anderson Ricardo Martinez
Cessionnaire d'origine	Adeza Biomedical Corporation Goldman Sachs Bank Usa Cytyc Surgical Products Limited Partnership R2 Technology, Inc. Hologic, Inc. Cytyc Corporation Direct Radiography Corp. Cytyc Prenatal Products Corp. Third Wave Technologies, Inc. Biolucent, Llc Cytyc Surgical Products Iii, Inc. Cytyc Surgical Products Ii Limited Partnership Suros Surgical Systems, Inc. Goldman Sachs Credit Partners L.P., As Collateral Agent Goldman Sachs Credit Partners L.P. Mmc/Gatx Partnership No. 1
Classification aux États-Unis	D24/223
Références	Citations hors brevets (53) Référencé par (1)

Liens externes	USPTO Cession USPTO Espacenet

Device for encasing an assay test strip

US D432244 S

Revendications

The ornamental design for a device for encasing an assay test strip, as shown and described.

Description

FIG. 1 is a perspective view of a diagnostic detection device for encasing an assay test strip showing our new design;

FIG. 2 is an end elevational view thereof;

FIG. 3 is a top plan view thereof;

FIG. 4 is a bottom plan view thereof; and,

FIG. 5 is a side elevational view thereof, both sides being similar.

Citations hors brevets

Référence
1	"Artificial Intelligence Systems in Routine Clinical Use", (available on http://www.gretmar.com/ailist/list.html on Nov. 21, 1996).
2	"BarCode 1; Code 128 Specification Page", (available on http://www.adams1.com/pub/russadam/128code.html on Apr. 14, 1998).
3	"Code 39 Symbology", (available on http://www.abetech.com/abetech/ab .../3d40bf6c892a1f6a8625645100586c88 on Apr. 14, 1998).
4	"Neural Informatics Pearls of Wisdom", (available on http://www.-smi.stanford.edu/people/...hysiology/Neuro.sub.-- Pearls.html#ANN-app on Nov. 21, 1996).
5	Alvager, T., et al., "The Use of Artificial Neural Networks in Biomedial Technologies: An Introduction", Biomed. Instr. Tech., 315-322 (1994).
6	Baxt, W.G. and White, H., "Bootstrapping Confidence Intervals for Clinical Input Variable Effects in a Network Trained to Identify the Presence of Acute Myocardial Infarction", Neur. Comp., 7:624-638 (1995).
7	Baxt, W.G., "A Neural Network Trained to Identify the Presence of Myocaridal Infarction Bases Some Decisions on Clinical Associations that Differ from Accepted Clinical Teaching", Med. Decis. Making, 14:217-222 (1994).
8	Baxt, W.G., "Analysis of the Clinical Variables Driving Decision in an Artificial Neural Network Trained to Identify the Presence of Myocardial Infarction", Ann. Emerg. Med., 21(12):1439-1444 (1992).
9	Baxt, W.G., "Application of Artificial Neural Networks to Clinical Medicine", The Lancet, 346:1135-1138 (1995).
10	Baxt, W.G., "Complexity, Chaos and Human Physiology: The Justification for Non-Linear Neural Computational Analysis", Cancer Lett., 77:85-93 (1994).
11	Baxt, W.G., "Improving the Accuracy of an Artificial Neural Network Using Multiple Differently Trained Networks", Neur. Comp., 4:772-780 (1992).
12	Baxt, W.G., "Use of an Articifial Neural Network for Data Analysis in Clinical Decision-Making: The Diagnosis of Acute Coronary Occlusion", Neur. Comp., 2:480-489 (1990).
13	Baxt, W.G., "Use of an Artificial Neural Network for the Diagnosis of Myocardial Infarction", Ann. Int. Med., 115:843-848 (1991).
14	Beksac, M.S. et al., "An Artificial Intelligent Diagnostic System with Neural Networks to Determine Genetical Disorders and Fetal Health by Using Maternal Serum Markets", Eur. Jour. Ob. Gyn. Reprod. Bio., 59:131-136 (1995).
15	Benediktsson, J.A. et al., "Parallel Consensual Neural Networks with Optimally Weighted Output", Proc. World Cong. Neur. Networks, 3:129-137 (1994).
16	BioComp Systems, Inc., "Systems that Learn, Adapt and Evolve", (available on http.//www.bio-comp.com/products.htm on Nov. 21, 1996).
17	Blinowska, A. et al., "Diagnostica--A Bayesian Decision-Aid System--Applied to Hypertension Diagnosis", IEEE Transact. Biomed. Eng., 40(3):230-235 (1993).
18	Brickley, M.R. and Shepherd, J.P., "Performance of a Neural Network Trained to Make Third-molar Treatment-planning Decisions", Med. Decis. Making, 16:153-160 (1996).
19	Creasy, R.. and Resnik, R., "Maternal-Fetal Medicine: Principles and Practice", Ch.36, Sect. 18, p. 657, Harcourt, Brace, Jovanovich, Inc., 1989.
20	Davis, R. et al., "Production Rules as a Representation for a Knowledge-Based Consultation Program", Artif. Intel., 8:15-45 (1977).
21	Diller, W., "Horus' Computer-Enhanced Diagnostics", IN VIVO: Business and Medicine Report, pp. 3-10 (1997).
22	Fahlman, S.E. and Lebiere, C., "The Cascade-Correlation Learning Architecture", Adv. Neur. Informat. Proc. Syst., 2;524-532 (1989).
23	Fahlman, S.E., "Faster-Learning Variations on Back-Propagation: An Empirical Study", Proc. 1988 Connectionist Models Summer School, Pittsburgh, pp. 38-51 (1988).
24	Geoghegan, W.D. and Ackerman, G.A., "Adsorption of Horseradish Peroxidase, Ovomucoid and Anti-Immunoglobulin to Colloidal Gold for the Indirect Detection of Concanavalin A, Wheat Germ Agglutinin and Goat Anti-Human Immunoglobulin G on Cell Surfaces at the Electron Microscopic Level: A New Method, Theory and Application", Jour. Hist. Cytochem., 25(11):1187-1200 (1977).
25	Kahn, C.E. et al., "Mammonet: Mammography Decision Support System", (available at http://www.mcw.edu/midas/mammo.html on Nov. 21, 1996).
26	Keller, P.E., "Artificial Neural Networks in Medicine", Handout / Technology brief, Pacific Northwest Laboratory.
27	Kim, J. et al., "Ensemble Competitive Learning Neural Networks with Reduced Input Dimension", Int. J. Neur. Syst., 6(2):133-142 (1995).
28	Kol, S. et al., "Interpretation of Nonstress Tests by an Artificial Neural Network", Am. J. Obstet. Gynecol., 172(5):1372-1379 (1995).
29	LaPuerta, P. et al., "Use of Neural Networks in Predicting the Risk of Coronary Artery Disease", Comp. Biomed. Res., 28:38-52 (1995).
30	Maclin, P.S. et al., "Using Neural Networks to Diagnose Cancer", J. Med. Syst., 15(1):11-19 (1991).
31	Matsuura, H. and Hakomori, S., "The Oncofetal Domain of Fibronectin Defined by Monoclonal Antibody FDC-6: Its Presence in Fibronectins from Fetal and Tumor Tissues and Its Absence in Those Normal Adult Tissues and Plasma", Proc Natl. Acad. Sci. USA, 82:6517-6521 (1985).
32	Mobley, B.A. et al., "Artificial Neural Network Predictions of Lengths of Stay on a Post-Coronary Care Unit", Heart Lung, 24(3):251-256 (1995).
33	Modai, I. et al., "Clinical Decisions for Psychiatric Inpatients and their Evaluation by a Trained Neural Network", Meth. Inform. Med., 32(5):396-399 (1993).
34	Moneta, C. et al., "Automated Diagnosis and Disease Characterization using Neural Network Analysis", IEEE Intl. Conf. Systs., Man. Cybernetics, USA, 1:123-128 (1992).
35	Nejad, A.F. and Gedeon, T.D., "Significance Measures and Data Dependency in Classification Methods", IEEE Intl. Conf. Neur. Network Proceedings, Australia, 4:1816-1822 (1995).
36	Ota, H. and Maki, M., "Evaluation of Autoantibody and CA125 in the Diagnosis of Endometriosis or Adenomyosis", Med. Sci. Res., 18:309-310 (1990).
37	Pattichis, C.S. et al., "Neural Network Models in EMG Diagnosis", IEEE Trans. Biomed. Engin., 42:486-495 (1995).
38	Penny, W. and Frost, D., "Neural Networks in Clinical Medicine", Med. Decis. Making, 16:386-398 (1996).
39	Pollak, V. and Boulton, A.A., "An Experimental High-Performance Photodensitometer for Quantitative Chromatography", J. Chromat., 115:335-347 (1975).
40	Press, W.H. et al., eds., "Numerical Recipes in C", Cambridge University Press, Second Edition, 1992.
41	Rogers, S.K. et al., "Artificial Neural Networks for Early Detection and Diagnosis of Cancer", 77:79-83 (1994).
42	Siganos, D., "Neural Networks in Medicine", (available at http://scorch.doc.ic.ac.uk/˜nd/surprise.sub.-- 96/journal/vol2/ds12/article2.html on Nov. 21, 1996).
43	Snow, P.B. et al., "Artificial Neural Networks in the Diagnosis and Prognosis of Prostate Cancer: A Pilot Study", J. Urol., 152:1923-26 (1994).
44	Solms, F. et al., "A Neural Network Diagnostic Tool for the Chronic Fatigue Syndrome", International Conference on Neural Networks, Paper No. 108 (1996).
45	Stamey, T.A., "ProstAsure™: An Information Resource", (available at http://www.labcorp.com/prost3.htm on Nov. 21, 1996).
46	Stephenson, J., "RAMP: A Quantitative Immunoassay Platform Takes Shape", IVD Tech., pp. 51-56 (1996).
47	Turner, D.D. and Garrett, B.A., "Coronary Artery Disease Diagnosis", Technology handout, (available on http://www.emsl.gov:2080/docs/cie/techbrief/CAD.techbrief.html on Nov. 21, 1996).
48	Utans, J. and Moody, J., "Selecting Neural Network Architectures via the Prediction Risk: Application to Corporate Bond Rating Prediction", Proceedings of the First International Conference on Artificial Intelligence Applications on Wall Street, Washington, D.C., IEEE Computer Society Press, pp. 35-41 (1991).
49	Utans, J. et al., "Input Variable Selection for Neural Networks: Application to Predicting the U.S. Business Cycle", IEEE, pp. 118-122 (1995).
50	Weinstein, J.N. et al., "Neural Networks in the Biomedical Sciences: A Survey of 386 Publicaitons Since the Beginning of 1991", pp. 121-126.
51	Widman, L.E., "Expert Systems in Medicine", (available on http://amplatz.uokhsc.edu/acc95-expert-systems.html on Nov. 21, 1996).
52	Wilding, P. et al., "Application of Backpropagation Neural Networks to Diagnosis of Breast and Ovarian Cancer", Cancer Lett., 77:145-153 (1994).
53	Young, G.P., "Diagnosis of Acute Cardiac Ischemia", (available on http://www.library.ucs... 1/Originals/young.html on Nov. 21, 1996).

Référencé par

Brevet citant	Date de dépôt	Date de publication	Déposant	Titre
US7879293	30 nov. 2001	1 févr. 2011	Orasure Technologies, Inc.	Sample collector and test device

Brevets