A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy
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{"title"=>"A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy", "type"=>"journal", "authors"=>[{"first_name"=>"Sam", "last_name"=>"Mavandadi", "scopus_author_id"=>"6505893736"}, {"first_name"=>"Steve", "last_name"=>"Feng", "scopus_author_id"=>"53663536400"}, {"first_name"=>"Frank", "last_name"=>"Yu", "scopus_author_id"=>"53664875800"}, {"first_name"=>"Stoyan", "last_name"=>"Dimitrov", "scopus_author_id"=>"55216794800"}, {"first_name"=>"Karin", "last_name"=>"Nielsen-Saines", "scopus_author_id"=>"16316824300"}, {"first_name"=>"William R.", "last_name"=>"Prescott", "scopus_author_id"=>"7006580915"}, {"first_name"=>"Aydogan", "last_name"=>"Ozcan", "scopus_author_id"=>"7005667692"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84867409526", "doi"=>"10.1371/journal.pone.0046192", "issn"=>"19326203", "pui"=>"365840924", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"23071544", "scopus"=>"2-s2.0-84867409526"}, "id"=>"757a0c02-b36a-3b9c-953e-7aeee559137f", "abstract"=>"We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing 'slide-level' diagnosis by using individual 'cell-level' diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.", "link"=>"http://www.mendeley.com/research/mathematical-framework-combining-decisions-multiple-experts-toward-accurate-remote-diagnosis-malaria", "reader_count"=>37, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>10, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>3, "Student > Master"=>7, "Other"=>2, "Student > Bachelor"=>2, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>10, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>3, "Student > Master"=>7, "Other"=>2, "Student > Bachelor"=>2, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>7, "Unspecified"=>4, "Mathematics"=>1, "Medicine and Dentistry"=>11, "Agricultural and Biological Sciences"=>2, "Arts and Humanities"=>1, "Physics and Astronomy"=>3, "Chemical Engineering"=>1, "Chemistry"=>1, "Social Sciences"=>1, "Computer Science"=>4, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>7}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>11}, "Chemistry"=>{"Chemistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>2}, "Computer Science"=>{"Computer Science"=>4}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>4}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"United States"=>2, "United Kingdom"=>1, "India"=>1}, "group_count"=>5}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/560074"], "description"=>"<p>Each observation made by the expert can take one of three category values from . The parameters governing the model are and , where is the true category of the observed data point, and and correspond to the expert labelling the data point as or , respectively.</p>", "links"=>[], "tags"=>["cell biology", "hematology", "computer science", "pathology", "Non-clinical medicine", "Infectious diseases", "Computational biology", "science policy", "mathematics"], "article_id"=>230555, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.t001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mixture_Model_Parameters_/230555", "title"=>"Mixture Model Parameters.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-19 21:50:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/559358"], "description"=>"<p>More than 8,000 RBC images were remotely presented to these experts, using the interface that is illustrated in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0046192#pone-0046192-g001\" target=\"_blank\">Figure 1</a>. For example, at least five out of nine experts agree on 97% of images labelled as negative, 64% labelled as positive, and 7% labelled as questionable; whereas only one out of nine experts at any given time agrees on the full set of labels (i.e., no two experts agree completely!). Note that these percentages are based on individual RBC images. For example, in the 3 column, it is not the same 3 experts who agree on the images but possibly different sets of 3 experts for different images.</p>", "links"=>[], "tags"=>["cell biology", "hematology", "computer science", "pathology", "Non-clinical medicine", "Infectious diseases", "Computational biology", "science policy", "mathematics"], "article_id"=>229833, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g004", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experimental_results_on_the_level_of_agreement_among_experts_/229833", "title"=>"Experimental results on the level of agreement among experts.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:46:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/559775"], "description"=>"<p>Each observation made by the expert can take one of three category values from . The parameters governing the model are and , where is the true category of the observed data point, and and correspond to the expert labelling the data point as 0 or 1, respectively. Please refer to the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0046192#s2\" target=\"_blank\">Methods</a> Section for further details.</p>", "links"=>[], "tags"=>["cells", "classified"], "article_id"=>230266, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g008", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sample_cells_classified_by_the_proposed_methodology_/230266", "title"=>"Sample cells classified by the proposed methodology.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:48:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/559652"], "description"=>"<p>The metrics are calculated after combining the responses of all the experts using EM and then assuming the results to be correct. , , , , where , and correspond to the number of true positive, true negative, false positive, and false negative labels respectively.</p>", "links"=>[], "tags"=>["metrics"], "article_id"=>230147, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g007", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experimental_performance_metrics_of_the_experts_/230147", "title"=>"Experimental performance metrics of the experts.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:48:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/559549"], "description"=>"<p>We can see that the combined accuracy (in green) is always higher than the maximum accuracy of the ensemble. Refer to the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0046192#s2\" target=\"_blank\">Methods</a> section for details.</p>", "links"=>[], "tags"=>["simulated", "experts", "varying", "ensemble"], "article_id"=>230036, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g006", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_results_from_9_simulated_experts_with_varying_average_ensemble_accuracies_/230036", "title"=>"Performance results from 9 simulated experts with varying average ensemble accuracies.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:47:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/559455"], "description"=>"<p>More than 8,000 RBC images were separately presented to these experts, using the interface that is illustrated in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0046192#pone-0046192-g001\" target=\"_blank\">Figure 1</a>. For example, expert 1 changes her/his decision regarding what s/he labelled as negative 1.6% of the time. Similarly s/he changed her/his mind for 1.3% and 1.8% of the positive and questionable images, respectively.</p>", "links"=>[], "tags"=>["cell biology", "hematology", "computer science", "pathology", "Non-clinical medicine", "Infectious diseases", "Computational biology", "science policy", "mathematics"], "article_id"=>229935, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g005", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experimental_results_on_the_level_of_self_inconsistency_of_each_expert_within_each_category_/229935", "title"=>"Experimental results on the level of <i>self-inconsistency</i> of each expert within each category.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:47:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/559060"], "description"=>"<p>Each expert is allowed to navigate through the database of cell images, eliminating the infected cells and marking those that are questionable (i.e., cannot be reliably labelled as infected or uninfected).</p>", "links"=>[], "tags"=>["browser-based", "interface"], "article_id"=>229547, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_browser_based_interface_for_remote_cell_labelling_/229547", "title"=>"The browser-based interface for remote cell labelling.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:45:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/559187"], "description"=>"<p>There are a total of images with possible labels from being sent to experts. The expert labels each image with a certain probability . The final dataset consists of an matrix of values from the set .</p>", "links"=>[], "tags"=>["cell biology", "hematology", "computer science", "pathology", "Non-clinical medicine", "Infectious diseases", "Computational biology", "science policy", "mathematics"], "article_id"=>229668, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g002", "stats"=>{"downloads"=>2, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Forward_model_of_the_proposed_setup_/229668", "title"=>"Forward model of the proposed setup.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:45:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/559979"], "description"=>"<p>A) parasitemia . B) parasitem .</p>", "links"=>[], "tags"=>["curves", "smear-level"], "article_id"=>230465, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g009", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_ROC_curves_for_smear_level_diagnosis_/230465", "title"=>"ROC curves for smear-level diagnosis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:50:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/559264"], "description"=>"<p>The expert responses are treated as the observed variables and the true image labels as the latent variables in a mixture model with parameters . Expectation Maximisation (EM) is used to obtain the Maximum Likelihood solution to the data.</p>", "links"=>[], "tags"=>["cell biology", "hematology", "computer science", "pathology", "Non-clinical medicine", "Infectious diseases", "Computational biology", "science policy", "mathematics"], "article_id"=>229746, "categories"=>["Science Policy", "Cell Biology", "Hematology", "Infectious Diseases", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Medicine"], "users"=>["Sam Mavandadi", "Steve Feng", "Frank Yu", "Stoyan Dimitrov", "Karin Nielsen-Saines", "William R. Prescott", "Aydogan Ozcan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046192.g003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Decoding_model_of_the_proposed_setup_/229746", "title"=>"Decoding model of the proposed setup.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 21:46:20"}

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Relative Metric

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