{"id":"https://openalex.org/W7220699983","doi":"https://doi.org/10.48550/arxiv.2610.06355","title":"Latent Similarity Gaussian Processes: A Theory-Grounded Approach to Personalized Suicide-Risk Forecasting for Clinical Decision-Support","display_name":"Latent Similarity Gaussian Processes: A Theory-Grounded Approach to Personalized Suicide-Risk Forecasting for Clinical Decision-Support","publication_year":2026,"publication_date":"2026-10-05","ids":{"openalex":"https://openalex.org/W7220699983","doi":"https://doi.org/10.48550/arxiv.2610.06355"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.06355","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06355","pdf_url":"https://arxiv.org/pdf/2610.06355","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.06355","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031215668","display_name":"Yaniv Yacoby","orcid":"https://orcid.org/0000-0002-0421-1070","observed_orcids":["https://orcid.org/0000-0002-0421-1070"]},"institutions":[{"id":"https://openalex.org/I189731429","display_name":"Wellesley College","ror":"https://ror.org/01srpnj69","country_code":"US","type":"education","lineage":["https://openalex.org/I189731429"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yacoby, Yaniv","raw_affiliation_strings":["Wellesley College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wellesley College","institution_ids":["https://openalex.org/I189731429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114910588","display_name":"Weiwei Pan","orcid":"https://orcid.org/0000-0001-8323-861X","observed_orcids":["https://orcid.org/0000-0001-8323-861X"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I189731429","display_name":"Wellesley College","ror":"https://ror.org/01srpnj69","country_code":"US","type":"education","lineage":["https://openalex.org/I189731429"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pan, Weiwei","raw_affiliation_strings":["Harvard University","Wellesley College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"Wellesley College","institution_ids":["https://openalex.org/I189731429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136431588","display_name":"Hope Neveux","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I189731429","display_name":"Wellesley College","ror":"https://ror.org/01srpnj69","country_code":"US","type":"education","lineage":["https://openalex.org/I189731429"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neveux, Hope","raw_affiliation_strings":["Harvard University","Wellesley College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"Wellesley College","institution_ids":["https://openalex.org/I189731429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083274652","display_name":"Taylor C. McGuire","orcid":"https://orcid.org/0000-0002-2020-5746","observed_orcids":["https://orcid.org/0000-0002-2020-5746"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I189731429","display_name":"Wellesley College","ror":"https://ror.org/01srpnj69","country_code":"US","type":"education","lineage":["https://openalex.org/I189731429"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"McGuire, Taylor C.","raw_affiliation_strings":["Harvard University","Wellesley College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"Wellesley College","institution_ids":["https://openalex.org/I189731429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022537224","display_name":"Franchesca Castro\u2010Ramirez","orcid":"https://orcid.org/0000-0001-5643-1510","observed_orcids":["https://orcid.org/0000-0001-5643-1510"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Castro-Ramirez, Franchesca","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066272658","display_name":"Anushka Patel","orcid":"https://orcid.org/0000-0002-8298-1804","observed_orcids":["https://orcid.org/0000-0002-8298-1804"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Patel, Anushka R.","raw_affiliation_strings":["Harvard Medical School Massachusetts General Hospital","Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard Medical School Massachusetts General Hospital","institution_ids":["https://openalex.org/I136199984","https://openalex.org/I4210087915"]},{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5157676980","display_name":"Matthew K. Nock","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nock, Matthew K.","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10376","display_name":"Suicide and Self-Harm Studies","score":0.7192000150680542,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10376","display_name":"Suicide and Self-Harm Studies","score":0.7192000150680542,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.10700000077486038,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.05169999971985817,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/similarity-kernels","display_name":"similarity kernels","score":0.7649999856948853},{"id":"https://openalex.org/keywords/personalized-risk-prediction","display_name":"personalized risk prediction","score":0.7990000247955322},{"id":"https://openalex.org/keywords/clinical-decision-support","display_name":"clinical decision support","score":0.8299999833106995},{"id":"https://openalex.org/keywords/intensive-longitudinal-data","display_name":"intensive longitudinal data","score":0.8389999866485596},{"id":"https://openalex.org/keywords/mean-field-variational-inference","display_name":"mean-field variational inference","score":0.8379999995231628},{"id":"https://openalex.org/keywords/hierarchical-models","display_name":"hierarchical models","score":0.6499999761581421}],"concepts":[{"id":"https://openalex.org/C179034447","wikidata":"https://www.wikidata.org/wiki/Q2621675","display_name":"Nomothetic and idiographic","level":2,"score":0.8269000053405762},{"id":"https://openalex.org/C153327018","wikidata":"https://www.wikidata.org/wiki/Q3496424","display_name":"Nomothetic","level":3,"score":0.794700026512146},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7558000087738037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5324000120162964},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5023000240325928},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4828000068664551},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41749998927116394},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4108999967575073},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4007999897003174},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.38420000672340393},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.37439998984336853},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3476000130176544},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32199999690055847},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C65965080","wikidata":"https://www.wikidata.org/wiki/Q1806885","display_name":"Latent variable model","level":3,"score":0.2694999873638153},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.06355","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06355","pdf_url":"https://arxiv.org/pdf/2610.06355","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2610.06355","doi":"https://doi.org/10.48550/arxiv.2610.06355","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.06355","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.06355","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06355","pdf_url":"https://arxiv.org/pdf/2610.06355","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8560000061988831,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G877982049","display_name":"Intensive longitudinal study of suicidal behaviors and related health outcomes","funder_award_id":"U01MH116928","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7220699983.pdf","grobid_xml":"https://content.openalex.org/works/W7220699983.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W2745847531","https://openalex.org/W3043747271"],"related_works":["https://openalex.org/W7106654381","https://openalex.org/W4403734691","https://openalex.org/W4328136066","https://openalex.org/W4407010483","https://openalex.org/W4399437505","https://openalex.org/W7119203892","https://openalex.org/W2031961563","https://openalex.org/W6991137836","https://openalex.org/W2594274997","https://openalex.org/W7030032869"],"abstract_inverted_index":{"Forecasting":[0],"suicide":[1,99],"risk":[2,54,111],"is":[3],"difficult":[4],"due":[5],"to":[6,36,85],"the":[7,13,76,114],"high":[8],"heterogeneity":[9],"of":[10,17],"patients":[11,30],"and":[12,40,61,92,106],"low":[14],"base":[15],"rate":[16],"suicide-related":[18],"events":[19],"(SREs).":[20],"We":[21],"present":[22],"Latent":[23],"Similarity":[24,71],"Gaussian":[25],"Processes":[26],"(LSGPs),":[27],"which":[28],"embed":[29],"in":[31,117],"a":[32,90],"continuous":[33],"latent":[34,48],"space":[35],"jointly":[37],"model":[38],"similarity":[39],"forecast":[41],"risk.":[42],"By":[43],"selectively":[44],"drawing":[45],"information":[46],"from":[47],"peers,":[49],"LSGPs":[50,84,102],"better":[51],"capture":[52],"individualized":[53],"trajectories,":[55],"generalizing":[56],"nomothetic":[57,86],"(pooled),":[58],"idiographic":[59],"(per-patient),":[60],"hierarchical":[62,107],"frameworks.":[63],"Our":[64],"contributions":[65],"are:":[66],"(1)":[67],"an":[68],"identifiable":[69],"two-channel":[70],"Kernel;":[72],"(2)":[73],"proof":[74],"that":[75],"standard":[77],"model-fitting":[78],"algorithm,":[79],"mean-field":[80],"variational":[81],"inference,":[82],"collapses":[83],"models,":[87],"along":[88],"with":[89,113],"fix;":[91],"(3)":[93],"empirical":[94],"results":[95],"on":[96],"intensive":[97],"longitudinal":[98],"data":[100],"showing":[101],"outperform":[103],"nomothetic,":[104],"idiographic,":[105],"models":[108],"for":[109],"next-week":[110],"forecasting,":[112],"largest":[115],"gains":[116],"forecasting":[118],"first-occurrence":[119],"SREs.":[120]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-07T00:00:00"}