Evidence map›Paper›PMID 26158123›Full record

ArticleMachine learning and knowledge discovery in databases : European Conference, ECML PKDD ... : proceedings. ECML PKDD (Conference)

Support Vector Machines for Differential Prediction.

Finn Kuusisto, Vitor Santos Costa, Houssam Nassif, Elizabeth Burnside, David Page, Jude Shavlik

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Machine learning and knowledge discovery in databases : European Conference, ECML PKDD ... : proceedings. ECML PKDD (Conference). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling.Machine learning and knowledge discovery in databases : European Conference, ECML PKDD ... : proceedings. ECML PKDD (Conference)
    Article
  3. Support Vector Machines for Differential Prediction.Machine learning and knowledge discovery in databases : European Conference, ECML PKDD ... : proceedings. ECML PKDD (Conference)
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Finn KuusistoUniversity of Wisconsin - Madison, Madison, WI, USA.
Vitor Santos CostaUniversity of Porto, Porto, Portugal.
Houssam NassifAmazon, Seattle, WA, USA.
Elizabeth Burnside
David Page
Jude Shavlik

Funding

Machine Learning for Identifying Adverse Drug EventsR01GM097618 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI CALDWELL, MICHAEL DEFOIX, HANSEN, RICHARD A. · 2011 to 2018
$3.8M
Informatics Techniques to Optimize Mammography for Aging PopulationsR01CA165229 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI BURNSIDE, ELIZABETH S · 2012 to 2016
$1.7M
Integrating Machine Learning and Physician Expertise for Breast Cancer DiagnosisR01LM010921 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI BURNSIDE, ELIZABETH S · 2011 to 2014
$1.2M
NCI NIH HHS R01 CA165229NIGMS NIH HHS R01 GM097618NLM NIH HHS R01 LM010921
6 · The paper itself

Abstract

Machine learning is continually being applied to a growing set of fields, including the social sciences, business, and medicine. Some fields present problems that are not easily addressed using standard machine learning approaches and, in particular, there is growing interest in

Indexed as

support vector machineuplift modeling

Identifiers

PMID26158123
PMCPMC4492338

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.