-
1
-
-
0001086656
-
Reporting adverse drug reactions
-
Delamothe T (1992) Reporting adverse drug reactions. Br Med J 304: 465
-
(1992)
Br Med J
, vol.304
, pp. 465
-
-
Delamothe, T.1
-
2
-
-
0029885854
-
Impact and credibility of the WHO adverse reaction signals
-
Fucik H, Edwards IR (1996) Impact and credibility of the WHO adverse reaction signals. Drug Inf J 30: 461-464
-
(1996)
Drug Inf J
, vol.30
, pp. 461-464
-
-
Fucik, H.1
Edwards, I.R.2
-
3
-
-
0030787821
-
Principles of signal detection in pharmacovigilance
-
Meyboom RHB, Egberts ACG, Edwards IR, Hekster YA, de Koning FHP, Gribnau FWJ (1997) Principles of signal detection in pharmacovigilance. Drug Saf 16: 355-365
-
(1997)
Drug Saf
, vol.16
, pp. 355-365
-
-
Meyboom, R.H.B.1
Egberts, A.C.G.2
Edwards, I.R.3
Hekster, Y.A.4
De Koning, F.H.P.5
Gribnau, F.W.J.6
-
4
-
-
0004593124
-
-
Elsevier, Amsterdam
-
Bégaud B, Chaslerie A, Fourrier A, Haramburu F, Miremont G (1993) Methodological approaches in pharmacoepidemiology: application to spontaneous reporting. Elsevier, Amsterdam
-
(1993)
Methodological Approaches in Pharmacoepidemiology: Application to Spontaneous Reporting
-
-
Bégaud, B.1
Chaslerie, A.2
Fourrier, A.3
Haramburu, F.4
Miremont, G.5
-
5
-
-
0015944767
-
Systematic signalling of adverse reactions to drugs
-
Finney DJ (1974) Systematic signalling of adverse reactions to drugs. Methods Inf Med 13: 1-10
-
(1974)
Methods Inf Med
, vol.13
, pp. 1-10
-
-
Finney, D.J.1
-
8
-
-
0030135411
-
A higher order bayesian neural network with spiking units
-
Lansner A, Hoist A (1996) A higher order bayesian neural network with spiking units. Int J Neural Syst 7: 115-128
-
(1996)
Int J Neural Syst
, vol.7
, pp. 115-128
-
-
Lansner, A.1
Hoist, A.2
-
9
-
-
0002037186
-
A one-layer feedback artificial neural network with a bayesian learning rule
-
Lansner A, Ekeberg Ö (1989) A one-layer feedback artificial neural network with a bayesian learning rule. Int J Neural Syst 1: 77-87
-
(1989)
Int J Neural Syst
, vol.1
, pp. 77-87
-
-
Lansner, A.1
Ekeberg, Ö.2
-
11
-
-
15144340020
-
A higher order neural network for classification and diagnosis
-
Gammerman A (ed) Wiley, Chichester
-
Holst A, Lansner A (1996) A higher order neural network for classification and diagnosis. In: Gammerman A (ed) Computational learning and probabilistic reasoning. Wiley, Chichester, pp 199-209
-
(1996)
Computational Learning and Probabilistic Reasoning
, pp. 199-209
-
-
Holst, A.1
Lansner, A.2
-
12
-
-
0027653442
-
A flexible and fault tolerant query-reply system based on a Bayesian neural network
-
Holst A, Lansner A (1993) A flexible and fault tolerant query-reply system based on a Bayesian neural network. Int J Neural Syst 4: 257-267
-
(1993)
Int J Neural Syst
, vol.4
, pp. 257-267
-
-
Holst, A.1
Lansner, A.2
-
13
-
-
14844362013
-
Pulp quality modelling using bayesian mixture density neural networks
-
Orre R, Lansner A (1996) Pulp quality modelling using bayesian mixture density neural networks. J Syst Eng 6: 128-136
-
(1996)
J Syst Eng
, vol.6
, pp. 128-136
-
-
Orre, R.1
Lansner, A.2
-
15
-
-
4344578226
-
Bayesian networks for data mining
-
Heckerman D (1997) Bayesian networks for data mining. Data Mining Knowl Discovery 1: 79-119
-
(1997)
Data Mining Knowl Discovery
, vol.1
, pp. 79-119
-
-
Heckerman, D.1
-
16
-
-
0020635959
-
Prikkelhoest door gebruik van captopril
-
Knoben JM (1983) Prikkelhoest door gebruik van captopril. Ned Tijdsch Geneeskd 127: 1306
-
(1983)
Ned Tijdsch Geneeskd
, vol.127
, pp. 1306
-
-
Knoben, J.M.1
-
17
-
-
0026591053
-
WHO's role in international ADR monitoring
-
ten Ham M (1992) WHO's role in international ADR monitoring. Post Mark Surveillance 5: 223-230
-
(1992)
Post Mark Surveillance
, vol.5
, pp. 223-230
-
-
Ten Ham, M.1
|