Search

Your search keyword '"van der Schaar M"' showing total 19 results
Start Over Author "van der Schaar M" Publication Type Electronic Resources
19 results on '"van der Schaar M"'

1. Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review

Author

Jones, OT, Matin, RN, van der Schaar, M, Bhayankaram, KP, Ranmuthu, CK, Islam, MS, Behiyat, D, Boscott, R, Calanzani, N, Emery, J, Williams, HC, Walter, FM, Jones, OT, Matin, RN, van der Schaar, M, Bhayankaram, KP, Ranmuthu, CK, Islam, MS, Behiyat, D, Boscott, R, Calanzani, N, Emery, J, Williams, HC, and Walter, FM

Abstract

Skin cancers occur commonly worldwide. The prognosis and disease burden are highly dependent on the cancer type and disease stage at diagnosis. We systematically reviewed studies on artificial intelligence and machine learning (AI/ML) algorithms that aim to facilitate the early diagnosis of skin cancers, focusing on their application in primary and community care settings. We searched MEDLINE, Embase, Scopus, and Web of Science (from Jan 1, 2000, to Aug 9, 2021) for all studies providing evidence on applying AI/ML algorithms to the early diagnosis of skin cancer, including all study designs and languages. The primary outcome was diagnostic accuracy of the algorithms for skin cancers. The secondary outcomes included an overview of AI/ML methods, evaluation approaches, cost-effectiveness, and acceptability to patients and clinicians. We identified 14 224 studies. Only two studies used data from clinical settings with a low prevalence of skin cancers. We reported data from all 272 studies that could be relevant in primary care. The primary outcomes showed reasonable mean diagnostic accuracy for melanoma (89·5% [range 59·7-100%]), squamous cell carcinoma (85·3% [71·0-97·8%]), and basal cell carcinoma (87·6% [70·0-99·7%]). The secondary outcomes showed a heterogeneity of AI/ML methods and study designs, with high amounts of incomplete reporting (eg, patient demographics and methods of data collection). Few studies used data on populations with a low prevalence of skin cancers to train and test their algorithms; therefore, the widespread adoption into community and primary care practice cannot currently be recommended until efficacy in these populations is shown. We did not identify any health economic, patient, or clinician acceptability data for any of the included studies. We propose a methodological checklist for use in the development of new AI/ML algorithms to detect skin cancer, to facilitate their design, evaluation, and implementation.

Published
2022

2. Learning Optimal Policies from Observational Data

Author

Atan, Onur, Zame, William R., van der Schaar, M, Atan, Onur, Zame, William R., and van der Schaar, M

Abstract

Choosing optimal (or at least better) policies is an important problem in domains from medicine to education to finance and many others. One approach to this problem is through controlled experiments/trials - but controlled experiments are expensive. Hence it is important to choose the best policies on the basis of observational data. This presents two difficult challenges: (i) missing counterfactuals, and (ii) selection bias. This paper presents theoretical bounds on estimation errors of counterfactuals from observational data by making connections to domain adaptation theory. It also presents a principled way of choosing optimal policies using domain adversarial neural networks. We illustrate the effectiveness of domain adversarial training together with various features of our algorithm on a semi-synthetic breast cancer dataset and a supervised UCI dataset (Statlog).

Published
2018

3. Sperm whale long-range echolocation sounds revealed by ANTARES, a deep-sea neutrino telescope

Author

Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres, Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada, Region Ile-de-France, Generalitat Valenciana, Université Sorbonne Paris Cité, Institut Universitaire de France, European Regional Development Fund, Instituto Nazionale di Fisica Nucleare, Conseil Régional Provence-Alpes-Côte d'Azur, Netherlands Organization for Scientific Research, Ministerio de Economía, Industria y Competitividad, Bundesministerium für Bildung und Forschung, Alemania, Centre National de la Recherche Scientifique, Francia, National Authority for Scientific Research, Rumanía, Council on grants of the President of the Russian Federation, Centre National pour la Recherche Scientifique et Technique, Marruecos, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Francia, Andre, M., Caballé, A., Van der Schaar, M., Solsona, A., Houégnigan, L., Zaugg, S., Sanchez, A. M., Castell, J. V., Solé, M., Vila, F., Djokic, D., Adrián Martínez, Silvia, Albert, A., Anghinolfi, M., Anton, G., Ardid Ramírez, Miguel, Felis-Enguix, Iván, Martínez Mora, Juan Antonio, Saldaña-Coscollar, María, Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres, Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada, Region Ile-de-France, Generalitat Valenciana, Université Sorbonne Paris Cité, Institut Universitaire de France, European Regional Development Fund, Instituto Nazionale di Fisica Nucleare, Conseil Régional Provence-Alpes-Côte d'Azur, Netherlands Organization for Scientific Research, Ministerio de Economía, Industria y Competitividad, Bundesministerium für Bildung und Forschung, Alemania, Centre National de la Recherche Scientifique, Francia, National Authority for Scientific Research, Rumanía, Council on grants of the President of the Russian Federation, Centre National pour la Recherche Scientifique et Technique, Marruecos, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Francia, Andre, M., Caballé, A., Van der Schaar, M., Solsona, A., Houégnigan, L., Zaugg, S., Sanchez, A. M., Castell, J. V., Solé, M., Vila, F., Djokic, D., Adrián Martínez, Silvia, Albert, A., Anghinolfi, M., Anton, G., Ardid Ramírez, Miguel, Felis-Enguix, Iván, Martínez Mora, Juan Antonio, and Saldaña-Coscollar, María

Abstract

[EN] Despite dedicated research has been carried out to adequately map the distribution of the sperm whale in the Mediterranean Sea, unlike other regions of the world, the species population status is still presently uncertain. The analysis of two years of continuous acoustic data provided by the ANTARES neutrino telescope revealed the year-round presence of sperm whales in the Ligurian Sea, probably associated with the availability of cephalopods in the region. The presence of the Ligurian Sea sperm whales was demonstrated through the real-time analysis of audio data streamed from a cabled-to- shore deep-sea observatory that allowed the hourly tracking of their long-range echolocation behaviour on the Internet. Interestingly, the same acoustic analysis indicated that the occurrence of surface shipping noise would apparently not condition the foraging behaviour of the sperm whale in the area, since shipping noise was almost always present when sperm whales were acoustically detected. The continuous presence of the sperm whale in the region confirms the ecological value of the Ligurian sea and the importance of ANTARES to help monitoring its ecosystems

Published
2017

4. Sperm whale long-range echolocation sounds revealed by ANTARES, a deep-sea neutrino telescope

Author

Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres, Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada, Region Ile-de-France, Agence Nationale de la Recherche, Francia, Generalitat Valenciana, Université Sorbonne Paris Cité, Institut Universitaire de France, European Regional Development Fund, Instituto Nazionale di Fisica Nucleare, Conseil Régional Provence-Alpes-Côte d'Azur, Netherlands Organization for Scientific Research, Bundesministerium für Bildung und Forschung, Alemania, Centre National de la Recherche Scientifique, Francia, National Authority for Scientific Research, Rumanía, Council on grants of the President of the Russian Federation, Centre National pour la Recherche Scientifique et Technique, Marruecos, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Francia, Ministerio de Ciencia e Innovación, Andre, M., Caballé, A., Van der Schaar, M., Solsona, A., Houégnigan, L., Zaugg, S., Sanchez, A. M., Castell, J. V., Solé, M., Vila, F., Djokic, D., Adrián Martínez, Silvia, Albert, A., Anghinolfi, M., Anton, G., Ardid Ramírez, Miguel, Felis-Enguix, Iván, Martínez Mora, Juan Antonio, Saldaña-Coscollar, María, Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres, Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada, Region Ile-de-France, Agence Nationale de la Recherche, Francia, Generalitat Valenciana, Université Sorbonne Paris Cité, Institut Universitaire de France, European Regional Development Fund, Instituto Nazionale di Fisica Nucleare, Conseil Régional Provence-Alpes-Côte d'Azur, Netherlands Organization for Scientific Research, Bundesministerium für Bildung und Forschung, Alemania, Centre National de la Recherche Scientifique, Francia, National Authority for Scientific Research, Rumanía, Council on grants of the President of the Russian Federation, Centre National pour la Recherche Scientifique et Technique, Marruecos, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Francia, Ministerio de Ciencia e Innovación, Andre, M., Caballé, A., Van der Schaar, M., Solsona, A., Houégnigan, L., Zaugg, S., Sanchez, A. M., Castell, J. V., Solé, M., Vila, F., Djokic, D., Adrián Martínez, Silvia, Albert, A., Anghinolfi, M., Anton, G., Ardid Ramírez, Miguel, Felis-Enguix, Iván, Martínez Mora, Juan Antonio, and Saldaña-Coscollar, María

Abstract

[EN] Despite dedicated research has been carried out to adequately map the distribution of the sperm whale in the Mediterranean Sea, unlike other regions of the world, the species population status is still presently uncertain. The analysis of two years of continuous acoustic data provided by the ANTARES neutrino telescope revealed the year-round presence of sperm whales in the Ligurian Sea, probably associated with the availability of cephalopods in the region. The presence of the Ligurian Sea sperm whales was demonstrated through the real-time analysis of audio data streamed from a cabled-to- shore deep-sea observatory that allowed the hourly tracking of their long-range echolocation behaviour on the Internet. Interestingly, the same acoustic analysis indicated that the occurrence of surface shipping noise would apparently not condition the foraging behaviour of the sperm whale in the area, since shipping noise was almost always present when sperm whales were acoustically detected. The continuous presence of the sperm whale in the region confirms the ecological value of the Ligurian sea and the importance of ANTARES to help monitoring its ecosystems

Published
2017

5. Sperm whale long-range echolocation sounds revealed by ANTARES, a deep-sea neutrino telescope

Author

André, M., Caballé, A., van der Schaar, M., Solsona, A., Houégnigan, L., Zaugg, S., Sánchez, A.M., Castell, J.V., Solé, M., Vila, F., Djokic, D., Adrián-Martínez, S., Albert, A., Anghinolfi, M., Anton, G., Ardid, M., Aubert, J.-J., Avgitas, T., Baret, B., Barrios-Martí, J., Basa, S., Bertin, V., Biagi, S., Bormuth, R., Bouwhuis, M.C., Bruijn, R., Brunner, J., Busto, J., Capone, A., Caramete, L., Carr, J., Celli, S., Chiarusi, T., Circella, M., Coleiro, A., Coniglione, R., Costantini, H., Coyle, P., Creusot, A., Deschamps, A., De Bonis, G., Distefano, C., Di Palma, I., Donzaud, C., Dornic, D., Drouhin, D., Eberl, T., El Bojaddaini, I., Elsässer, D., Enzenhöfer, A., Fehn, K., Felis, I., Fusco, L.A., Galatà, S., Gay, P., Geißelsöder, S., Geyer, K., Giordano, V., Gleixner, A., Glotin, H., Gracia-Ruiz, R., Graf, K., Hallmann, S., van Haren, H., Heijboer, A.J., Hello, Y., Hernandez-Rey, J.J., Hößl, J., Hofestädt, J., Hugon, C., Illuminati, G., James, C.W., de Jong, M., Jongen, M., Kadler, M., Kalekin, O., Katz, U., Kießling, D., Kouchner, A., Kreter, M., Kreykenbohm, I., Kulikovskiy, V., Lachaud, C., Lahmann, R., Lefèvre, D., Leonora, E., Loucatos, S., Marcelin, M., Margiotta, A., Marinelli, A., Martínez-Mora, J.A., Mathieu, A., Melis, K., Michael, T., Migliozzi, P., Moussa, A., Mueller, C., Nezri, E., Pavalas, G.E., Pellegrino, C., Perrina, C., Piattelli, P., Popa, V., Pradier, T., Racca, C., Riccobene, G., Roensch, K., Saldaña, M., Samtleben, D.F.E., Sanguineti, M., Sapienza, P., Schnabel, J., Schüssler, F., Seitz, T., Sieger, C., Spurio, M., Stolarczyk, T., Sánchez-Losa, A., Taiuti, M., Trovato, A., Tselengidou, M., Turpin, D., Tönnis, C., Vallage, B., Vallée, C., Van Elewyck, V., Vivolo, D., Wagner, S., Wilms, J., Zornoza, J.D., Zuniga, J., André, M., Caballé, A., van der Schaar, M., Solsona, A., Houégnigan, L., Zaugg, S., Sánchez, A.M., Castell, J.V., Solé, M., Vila, F., Djokic, D., Adrián-Martínez, S., Albert, A., Anghinolfi, M., Anton, G., Ardid, M., Aubert, J.-J., Avgitas, T., Baret, B., Barrios-Martí, J., Basa, S., Bertin, V., Biagi, S., Bormuth, R., Bouwhuis, M.C., Bruijn, R., Brunner, J., Busto, J., Capone, A., Caramete, L., Carr, J., Celli, S., Chiarusi, T., Circella, M., Coleiro, A., Coniglione, R., Costantini, H., Coyle, P., Creusot, A., Deschamps, A., De Bonis, G., Distefano, C., Di Palma, I., Donzaud, C., Dornic, D., Drouhin, D., Eberl, T., El Bojaddaini, I., Elsässer, D., Enzenhöfer, A., Fehn, K., Felis, I., Fusco, L.A., Galatà, S., Gay, P., Geißelsöder, S., Geyer, K., Giordano, V., Gleixner, A., Glotin, H., Gracia-Ruiz, R., Graf, K., Hallmann, S., van Haren, H., Heijboer, A.J., Hello, Y., Hernandez-Rey, J.J., Hößl, J., Hofestädt, J., Hugon, C., Illuminati, G., James, C.W., de Jong, M., Jongen, M., Kadler, M., Kalekin, O., Katz, U., Kießling, D., Kouchner, A., Kreter, M., Kreykenbohm, I., Kulikovskiy, V., Lachaud, C., Lahmann, R., Lefèvre, D., Leonora, E., Loucatos, S., Marcelin, M., Margiotta, A., Marinelli, A., Martínez-Mora, J.A., Mathieu, A., Melis, K., Michael, T., Migliozzi, P., Moussa, A., Mueller, C., Nezri, E., Pavalas, G.E., Pellegrino, C., Perrina, C., Piattelli, P., Popa, V., Pradier, T., Racca, C., Riccobene, G., Roensch, K., Saldaña, M., Samtleben, D.F.E., Sanguineti, M., Sapienza, P., Schnabel, J., Schüssler, F., Seitz, T., Sieger, C., Spurio, M., Stolarczyk, T., Sánchez-Losa, A., Taiuti, M., Trovato, A., Tselengidou, M., Turpin, D., Tönnis, C., Vallage, B., Vallée, C., Van Elewyck, V., Vivolo, D., Wagner, S., Wilms, J., Zornoza, J.D., and Zuniga, J.

Abstract

Despite dedicated research has been carried out to adequately map the distribution of the spermwhale in the Mediterranean Sea, unlike other regions of the world, the species population status is stillpresently uncertain. The analysis of two years of continuous acoustic data provided by the ANTARESneutrino telescope revealed the year-round presence of sperm whales in the Ligurian Sea, probablyassociated with the availability of cephalopods in the region. The presence of the Ligurian Sea spermwhales was demonstrated through the real-time analysis of audio data streamed from a cabled-toshoredeep-sea observatory that allowed the hourly tracking of their long-range echolocation behaviouron the Internet. Interestingly, the same acoustic analysis indicated that the occurrence of surfaceshipping noise would apparently not condition the foraging behaviour of the sperm whale in the area,since shipping noise was almost always present when sperm whales were acoustically detected. Thecontinuous presence of the sperm whale in the region confirms the ecological value of the Ligurian seaand the importance of ANTARES to help monitoring its ecosystems.

Published
2017

6. Sperm whale long-range echolocation sounds revealed by ANTARES, a deep-sea neutrino telescope

Author

André, M., Caballé, A., van der Schaar, M., Solsona, A., Houégnigan, L., Zaugg, S., Sánchez, A.M., Castell, J.V., Solé, M., Vila, F., Djokic, D., Adrián-Martínez, S., Albert, A., Anghinolfi, M., Anton, G., Ardid, M., Aubert, J.-J., Avgitas, T., Baret, B., Barrios-Martí, J., Basa, S., Bertin, V., Biagi, S., Bormuth, R., Bouwhuis, M.C., Bruijn, R., Brunner, J., Busto, J., Capone, A., Caramete, L., Carr, J., Celli, S., Chiarusi, T., Circella, M., Coleiro, A., Coniglione, R., Costantini, H., Coyle, P., Creusot, A., Deschamps, A., De Bonis, G., Distefano, C., Di Palma, I., Donzaud, C., Dornic, D., Drouhin, D., Eberl, T., El Bojaddaini, I., Elsässer, D., Enzenhöfer, A., Fehn, K., Felis, I., Fusco, L.A., Galatà, S., Gay, P., Geißelsöder, S., Geyer, K., Giordano, V., Gleixner, A., Glotin, H., Gracia-Ruiz, R., Graf, K., Hallmann, S., van Haren, H., Heijboer, A.J., Hello, Y., Hernandez-Rey, J.J., Hößl, J., Hofestädt, J., Hugon, C., Illuminati, G., James, C.W., de Jong, M., Jongen, M., Kadler, M., Kalekin, O., Katz, U., Kießling, D., Kouchner, A., Kreter, M., Kreykenbohm, I., Kulikovskiy, V., Lachaud, C., Lahmann, R., Lefèvre, D., Leonora, E., Loucatos, S., Marcelin, M., Margiotta, A., Marinelli, A., Martínez-Mora, J.A., Mathieu, A., Melis, K., Michael, T., Migliozzi, P., Moussa, A., Mueller, C., Nezri, E., Pavalas, G.E., Pellegrino, C., Perrina, C., Piattelli, P., Popa, V., Pradier, T., Racca, C., Riccobene, G., Roensch, K., Saldaña, M., Samtleben, D.F.E., Sanguineti, M., Sapienza, P., Schnabel, J., Schüssler, F., Seitz, T., Sieger, C., Spurio, M., Stolarczyk, T., Sánchez-Losa, A., Taiuti, M., Trovato, A., Tselengidou, M., Turpin, D., Tönnis, C., Vallage, B., Vallée, C., Van Elewyck, V., Vivolo, D., Wagner, S., Wilms, J., Zornoza, J.D., Zuniga, J., André, M., Caballé, A., van der Schaar, M., Solsona, A., Houégnigan, L., Zaugg, S., Sánchez, A.M., Castell, J.V., Solé, M., Vila, F., Djokic, D., Adrián-Martínez, S., Albert, A., Anghinolfi, M., Anton, G., Ardid, M., Aubert, J.-J., Avgitas, T., Baret, B., Barrios-Martí, J., Basa, S., Bertin, V., Biagi, S., Bormuth, R., Bouwhuis, M.C., Bruijn, R., Brunner, J., Busto, J., Capone, A., Caramete, L., Carr, J., Celli, S., Chiarusi, T., Circella, M., Coleiro, A., Coniglione, R., Costantini, H., Coyle, P., Creusot, A., Deschamps, A., De Bonis, G., Distefano, C., Di Palma, I., Donzaud, C., Dornic, D., Drouhin, D., Eberl, T., El Bojaddaini, I., Elsässer, D., Enzenhöfer, A., Fehn, K., Felis, I., Fusco, L.A., Galatà, S., Gay, P., Geißelsöder, S., Geyer, K., Giordano, V., Gleixner, A., Glotin, H., Gracia-Ruiz, R., Graf, K., Hallmann, S., van Haren, H., Heijboer, A.J., Hello, Y., Hernandez-Rey, J.J., Hößl, J., Hofestädt, J., Hugon, C., Illuminati, G., James, C.W., de Jong, M., Jongen, M., Kadler, M., Kalekin, O., Katz, U., Kießling, D., Kouchner, A., Kreter, M., Kreykenbohm, I., Kulikovskiy, V., Lachaud, C., Lahmann, R., Lefèvre, D., Leonora, E., Loucatos, S., Marcelin, M., Margiotta, A., Marinelli, A., Martínez-Mora, J.A., Mathieu, A., Melis, K., Michael, T., Migliozzi, P., Moussa, A., Mueller, C., Nezri, E., Pavalas, G.E., Pellegrino, C., Perrina, C., Piattelli, P., Popa, V., Pradier, T., Racca, C., Riccobene, G., Roensch, K., Saldaña, M., Samtleben, D.F.E., Sanguineti, M., Sapienza, P., Schnabel, J., Schüssler, F., Seitz, T., Sieger, C., Spurio, M., Stolarczyk, T., Sánchez-Losa, A., Taiuti, M., Trovato, A., Tselengidou, M., Turpin, D., Tönnis, C., Vallage, B., Vallée, C., Van Elewyck, V., Vivolo, D., Wagner, S., Wilms, J., Zornoza, J.D., and Zuniga, J.

Abstract

Despite dedicated research has been carried out to adequately map the distribution of the spermwhale in the Mediterranean Sea, unlike other regions of the world, the species population status is stillpresently uncertain. The analysis of two years of continuous acoustic data provided by the ANTARESneutrino telescope revealed the year-round presence of sperm whales in the Ligurian Sea, probablyassociated with the availability of cephalopods in the region. The presence of the Ligurian Sea spermwhales was demonstrated through the real-time analysis of audio data streamed from a cabled-toshoredeep-sea observatory that allowed the hourly tracking of their long-range echolocation behaviouron the Internet. Interestingly, the same acoustic analysis indicated that the occurrence of surfaceshipping noise would apparently not condition the foraging behaviour of the sperm whale in the area,since shipping noise was almost always present when sperm whales were acoustically detected. Thecontinuous presence of the sperm whale in the region confirms the ecological value of the Ligurian seaand the importance of ANTARES to help monitoring its ecosystems.

Published
2017

7. Sperm whale long-range echolocation sounds revealed by ANTARES, a deep-sea neutrino telescope

Author

Andre, M., Caballe, A., Van der Schaar, M., Solsona, A., Houegnigan, L., Zaugg, S., Sanchez, A., Castell, J., Sole, M., Vila, F., Djokic, D., Adrian-Martinez, S., Albert, A., Anghinolfi, M., Anton, G., Ardid, M., Aubert, J., Avgitas, T., Baret, B., Barrios-Marti, J., Basa, S., Bertin, V., Biagi, S., Bormuth, R., Bouwhuis, M., Bruijn, R., Brunner, J., Busto, J., Capone, A., Caramete, L., Carr, J., Celli, S., Chiarusi, T., Circella, M., Coleiro, A., Coniglione, R., Costantini, H., Coyle, P., Creusot, A., Deschamps, A., De Bonis, G., Distefano, C., Di Palma, I., Donzaud, C., Dornic, D., Drouhin, D., Eberl, T., El Bojaddaini, I., Elsaesser, D., Enzenhofer, A., Fehn, K., Felis, I., Fusco, L., Galata, S., Gay, P., Geisselsoeder, S., Geyer, K., Giordano, V., Gleixner, A., Glotin, H., Gracia-Ruiz, R., Graf, K., Hallmann, S., van Haren, H., Heijboer, A., Hello, Y., Hernandez-Rey, J., Hoessl, J., Hofestaedt, J., Hugon, C., Illuminati, G., James, Clancy, de Jong, M., Jongen, M., Kadler, M., Kalekin, O., Katz, U., Kiessling, D., Kouchner, A., Kreter, M., Kreykenbohm, I., Kulikovskiy, V., Lachaud, C., Lahmann, R., Lefevre, D., Leonora, E., Loucatos, S., Marcelin, M., Margiotta, A., Marinelli, A., Martinez-Mora, J., Mathieu, A., Melis, K., Michael, T., Migliozzi, P., Moussa, A., Mueller, C., Nezri, E., Pavalas, G., Pellegrino, C., Perrina, C., Piattelli, P., Popa, V., Pradier, T., Racca, C., Riccobene, G., Roensch, K., Saldana, M., Samtleben, D., Sanguineti, M., Sapienza, P., Schnabel, J., Schussler, F., Seitz, T., Sieger, C., Spurio, M., Stolarczyk, T., Sanchez-Losa, A., Taiuti, M., Trovato, A., Tselengidou, M., Turpin, D., Tonnis, C., Vallage, B., Vallee, C., Van Elewyck, V., Vivolo, D., Wagner, S., Wilms, J., Zornoza, J., Zuniga, J., Andre, M., Caballe, A., Van der Schaar, M., Solsona, A., Houegnigan, L., Zaugg, S., Sanchez, A., Castell, J., Sole, M., Vila, F., Djokic, D., Adrian-Martinez, S., Albert, A., Anghinolfi, M., Anton, G., Ardid, M., Aubert, J., Avgitas, T., Baret, B., Barrios-Marti, J., Basa, S., Bertin, V., Biagi, S., Bormuth, R., Bouwhuis, M., Bruijn, R., Brunner, J., Busto, J., Capone, A., Caramete, L., Carr, J., Celli, S., Chiarusi, T., Circella, M., Coleiro, A., Coniglione, R., Costantini, H., Coyle, P., Creusot, A., Deschamps, A., De Bonis, G., Distefano, C., Di Palma, I., Donzaud, C., Dornic, D., Drouhin, D., Eberl, T., El Bojaddaini, I., Elsaesser, D., Enzenhofer, A., Fehn, K., Felis, I., Fusco, L., Galata, S., Gay, P., Geisselsoeder, S., Geyer, K., Giordano, V., Gleixner, A., Glotin, H., Gracia-Ruiz, R., Graf, K., Hallmann, S., van Haren, H., Heijboer, A., Hello, Y., Hernandez-Rey, J., Hoessl, J., Hofestaedt, J., Hugon, C., Illuminati, G., James, Clancy, de Jong, M., Jongen, M., Kadler, M., Kalekin, O., Katz, U., Kiessling, D., Kouchner, A., Kreter, M., Kreykenbohm, I., Kulikovskiy, V., Lachaud, C., Lahmann, R., Lefevre, D., Leonora, E., Loucatos, S., Marcelin, M., Margiotta, A., Marinelli, A., Martinez-Mora, J., Mathieu, A., Melis, K., Michael, T., Migliozzi, P., Moussa, A., Mueller, C., Nezri, E., Pavalas, G., Pellegrino, C., Perrina, C., Piattelli, P., Popa, V., Pradier, T., Racca, C., Riccobene, G., Roensch, K., Saldana, M., Samtleben, D., Sanguineti, M., Sapienza, P., Schnabel, J., Schussler, F., Seitz, T., Sieger, C., Spurio, M., Stolarczyk, T., Sanchez-Losa, A., Taiuti, M., Trovato, A., Tselengidou, M., Turpin, D., Tonnis, C., Vallage, B., Vallee, C., Van Elewyck, V., Vivolo, D., Wagner, S., Wilms, J., Zornoza, J., and Zuniga, J.

Published
2017

8. Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors

Author

Yoon, J., Zame, W. R., Banerjee, A., Cadeiras, M., Alaa, A. M., van der Schaar, M., Yoon, J., Zame, W. R., Banerjee, A., Cadeiras, M., Alaa, A. M., and van der Schaar, M.

Abstract

Given the limited pool of donor organs, accurate predictions of survival on the wait list and post transplantation are crucial for cardiac transplantation decisions and policy. However, current clinical risk scores do not yield accurate predictions. We develop a new methodology (ToPs, Trees of Predictors) built on the principle that specific predictors should be used for specific clusters within the target population. ToPs discovers these specific clusters of patients and the specific predictor that perform best for each cluster. In comparison with current clinical risk scoring systems, our method provides significant improvements in the prediction of survival time on the wait list and post transplantation. For example, in terms of 3 month survival for patients who were on the US patient wait list in the period 1985 to 2015, our method achieves AUC of 0.847, the best commonly used clinical risk score (MAGGIC) achieves 0.630. In terms of 3 month survival/mortality predictions (in comparison to MAGGIC), holding specificity at 80.0 percents, our algorithm correctly predicts survival for 1,228 (26.0 percents more patients out of 4,723 who actually survived, holding sensitivity at 80.0 percents, our algorithm correctly predicts mortality for 839 (33.0 percents) more patients out of 2,542 who did not survive. Our method achieves similar improvements for other time horizons and for predictions post transplantation. Therefore, we offer a more accurate, personalized approach to survival analysis that can benefit patients, clinicians and policymakers in making clinical decisions and setting clinical policy. Because risk prediction is widely used in diagnostic and prognostic clinical decision making across diseases and clinical specialties, the implications of our methods are far reaching., Comment: Main manuscript: 20 pages, Supplementary materials: 13 pages, 5 figures, 3 tables. Submitted to Science Translational Medicine

Published
2017

9. ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening

Author

Alaa, AM, Alaa, AM, Moon, KH, Hsu, W, Van Der Schaar, M, Alaa, AM, Alaa, AM, Moon, KH, Hsu, W, and Van Der Schaar, M

Abstract

Breast cancer screening policies attempt to achieve timely diagnosis by regularly screening healthy women via various imaging tests. Various clinical decisions are needed to manage the screening process: selecting initial screening tests, interpreting test results, and deciding if further diagnostic tests are required. Current screening policies are guided by clinical practice guidelines (CPGs), which represent a 'one-size-fits-all' approach, designed to work well (on average) for a population, and can only offer coarse expert-based patient stratification that is not rigorously validated through data. Since the risks and benefits of screening tests are functions of each patient's features, personalized screening policies tailored to the features of individuals are desirable. To address this issue, we developed ConfidentCare: a computer-aided clinical decision support system that learns a personalized screening policy from electronic health record (EHR) data. By a 'personalized screening policy,' we mean a clustering of women's features, and a set of customized screening guidelines for each cluster. ConfidentCare operates by computing clusters of patients with similar features, then learning the 'best' screening procedure for each cluster using a supervised learning algorithm. The algorithm ensures that the learned screening policy satisfies a predefined accuracy requirement with a high level of confidence for every cluster. By applying ConfidentCare to real-world data, we show that it outperforms the current CPGs in terms of cost efficiency and false positive rates: a reduction of 31% in the false positive rate can be achieved.

Published
2016

10. ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening

Author

Alaa, AM, Alaa, AM, Moon, KH, Hsu, W, Van Der Schaar, M, Alaa, AM, Alaa, AM, Moon, KH, Hsu, W, and Van Der Schaar, M

Abstract

Breast cancer screening policies attempt to achieve timely diagnosis by regularly screening healthy women via various imaging tests. Various clinical decisions are needed to manage the screening process: selecting initial screening tests, interpreting test results, and deciding if further diagnostic tests are required. Current screening policies are guided by clinical practice guidelines (CPGs), which represent a 'one-size-fits-all' approach, designed to work well (on average) for a population, and can only offer coarse expert-based patient stratification that is not rigorously validated through data. Since the risks and benefits of screening tests are functions of each patient's features, personalized screening policies tailored to the features of individuals are desirable. To address this issue, we developed ConfidentCare: a computer-aided clinical decision support system that learns a personalized screening policy from electronic health record (EHR) data. By a 'personalized screening policy,' we mean a clustering of women's features, and a set of customized screening guidelines for each cluster. ConfidentCare operates by computing clusters of patients with similar features, then learning the 'best' screening procedure for each cluster using a supervised learning algorithm. The algorithm ensures that the learned screening policy satisfies a predefined accuracy requirement with a high level of confidence for every cluster. By applying ConfidentCare to real-world data, we show that it outperforms the current CPGs in terms of cost efficiency and false positive rates: a reduction of 31% in the false positive rate can be achieved.

Published
2016

11. ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening

Author

Alaa, AM, Alaa, AM, Moon, KH, Hsu, W, Van Der Schaar, M, Alaa, AM, Alaa, AM, Moon, KH, Hsu, W, and Van Der Schaar, M

Abstract

Breast cancer screening policies attempt to achieve timely diagnosis by regularly screening healthy women via various imaging tests. Various clinical decisions are needed to manage the screening process: selecting initial screening tests, interpreting test results, and deciding if further diagnostic tests are required. Current screening policies are guided by clinical practice guidelines (CPGs), which represent a 'one-size-fits-all' approach, designed to work well (on average) for a population, and can only offer coarse expert-based patient stratification that is not rigorously validated through data. Since the risks and benefits of screening tests are functions of each patient's features, personalized screening policies tailored to the features of individuals are desirable. To address this issue, we developed ConfidentCare: a computer-aided clinical decision support system that learns a personalized screening policy from electronic health record (EHR) data. By a 'personalized screening policy,' we mean a clustering of women's features, and a set of customized screening guidelines for each cluster. ConfidentCare operates by computing clusters of patients with similar features, then learning the 'best' screening procedure for each cluster using a supervised learning algorithm. The algorithm ensures that the learned screening policy satisfies a predefined accuracy requirement with a high level of confidence for every cluster. By applying ConfidentCare to real-world data, we show that it outperforms the current CPGs in terms of cost efficiency and false positive rates: a reduction of 31% in the false positive rate can be achieved.

Published
2016

16. A comparison of model and non-model based time-frequency transforms for sperm whale click classification

Author

Van der Schaar, M. (author), Delory, E. (author), Van der Weide, J. (author), Kamminga, C. (author), Goold, J.C. (author), Jaquet, N. (author), André, M. (author), Van der Schaar, M. (author), Delory, E. (author), Van der Weide, J. (author), Kamminga, C. (author), Goold, J.C. (author), Jaquet, N. (author), and André, M. (author)

Abstract

Electrical Engineering, Mathematics and Computer Science

Published
2007

17. A comparison of model and non-model based time-frequency transforms for sperm whale click classification

Author

Van der Schaar, M. (author), Delory, E. (author), Van der Weide, J. (author), Kamminga, C. (author), Goold, J.C. (author), Jaquet, N. (author), André, M. (author), Van der Schaar, M. (author), Delory, E. (author), Van der Weide, J. (author), Kamminga, C. (author), Goold, J.C. (author), Jaquet, N. (author), and André, M. (author)

Abstract

Electrical Engineering, Mathematics and Computer Science

Published
2007

Catalog

Books, media, physical & digital resources
See catalog results