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Record W3092368771 · doi:10.1002/pbc.28760

Training pediatric hematologist/oncologists for capacity building in Ethiopia

2020· article· en· W3092368771 on OpenAlexaff
Daniel Hailu, Diriba Fufa, Haileyesus Adam, Doreen Karimi Mutua, Wondwessen Bekele, Miguel Bonilla, Mahmut Celiker, Julia Challinor, Amit Dotan, Catherine Habashy, Prasanna N. Kumar, Carlos Rodríguez‐Galindo, Rabia Wali, Sheila Weitzman, Julie Broas, David N. Korones, Thomas Alexander, Aziza Shad

Bibliographic record

VenuePediatric Blood & Cancer · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsSubspecialtyMedicineCurriculumCapacity buildingTraining (meteorology)Pediatric cancerPediatric oncologyMedical educationFamily medicineNursingCancerEconomic growthInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: A considerable barrier to global pediatric oncology efforts has been the scarcity and even absence of trained professionals in many low- and middle-income countries, where the majority of children with cancer reside. In 2013, no dedicated pediatric hematology-oncology (PHO) programs existed in Ethiopia despite the estimated annual incidence of 6000-12000 cases. The Aslan Project initiative was established to fill this gap in order to improve pediatric cancer care in Ethiopia. A major objective was to increase subspecialty PHO-trained physicians who were committed to practicing locally and empowered to lead programmatic development. METHODS: We designed and implemented a PHO training curriculum to provide a robust educational and clinical experience within the existing resource-constrained environment in Ethiopia. Education relied on visiting PHO faculty, a training attachment abroad, and extraordinary initiative from trainees. RESULTS: Four physicians have completed comprehensive PHO subspecialty training based primarily in Ethiopia, and all have remained local. Former fellows are now leading two PHO centers in Ethiopia with a combined capacity of 64 inpatient beds and over 800 new diagnoses per year; an additional former fellow is developing a pediatric cancer program in Nairobi, Kenya. Two fellows currently are in training. Program leadership, teaching, and advocacy are being transitioned to these physicians. CONCLUSIONS: Despite myriad challenges, a subspecialty PHO training program was successfully implemented in a low-income country. PHO training in Ethiopia is approaching sustainability through human resource development, and is accelerating the growth of dedicated PHO services where none existed 7 years ago.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.106
GPT teacher head0.357
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2020
Admission routes1
Has abstractyes

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