DeepCertainty: Deep Learning for Contextual Diagnostic Uncertainty Measurement in Radiology Reports
DeepCertainty:放射学报告中上下文诊断不确定性测量的深度学习
基本信息
- 批准号:10593770
- 负责人:
- 金额:$ 18.84万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-09-01 至 2025-08-31
- 项目状态:未结题
- 来源:
- 关键词:Accident and Emergency departmentAddressAdoptedAdoptionAgreementAmerican College of RadiologyAngiographyAwarenessCalibrationCardiovascular systemCaringCategoriesCessation of lifeClinicalCommunicationComplexComputing MethodologiesDataData SetDecentralizationDiagnosisDiagnosticDiagnostic ErrorsDiagnostic ImagingDiagnostic testsDiseaseEffectivenessEmergency Department PhysicianEmergency Department patientEmergency SituationEmergency department visitEnsureEvaluationExclusionFeedbackFoundationsFundingGrainGuidelinesHealthcareHospitalizationImageImage AnalysisIndividualInpatientsInstitutionIntensive Care UnitsKnowledgeLanguageLearningLungMagnetic Resonance ImagingManualsMeasurementMeasuresMedicalModelingMorbidity - disease rateNatural Language ProcessingOutpatientsPatient CarePatientsPerceptionPersonsPhysiciansProcessPulmonary EmbolismQuality of CareRadiology SpecialtyReportingSamplingSemanticsSigns and SymptomsSpecific qualifier valueStandardizationStressStructureSystemTechnologyTestingTimeUncertaintyUnited StatesVariantWorkplaceX-Ray Computed Tomographyaccurate diagnosisaccurate diagnosticsadverse outcomeclinical decision-makingcomputerizedcost outcomesdeep learningdesignfuture implementationimaging modalityimpressionimprovedinnovationlexicalmortalityneuralpreventradiologistrapid diagnosisstatisticsunnecessary treatmentuser-friendly
项目摘要
PE becomes the third leading cause of cardiovascular-related death, and more than 500,000 cases of PE
occur in the United States (US) every year, resulting in approximately 200,000 deaths and hospitalization of
over 250,000 patients. Rapid and accurate diagnosis of PE are of paramount importance to ensure the highest
quality of care. Every year 1-2% of the 120 million emergency department (ED) patients in the US undergo
computed tomographic pulmonary angiography (CTPA) for PE. The referring physicians rely heavily on CTPA
reports diagnosing or excluding PEs. Clarity of the radiology report is one of the most critical qualities, and the
American College of Radiology has emphasized a need for precision communication in radiological reports.
Yet communicating uncertainty effectively in radiology reports is challenging. Referring physicians may
interpret radiologists’ textual expressions that convey diagnostic confidence differently than intended. The gap
between radiologists’ intended message and the referring physicians’ interpretation can not be completely
resolved through structured reporting or standardized lexicon. Unnecessary hedging language in CTPA reports
may further worsen the reporting ambiguity and may lead to inappropriate treatment of patients. Therefore, we
aim to develop a deep learning-based approach for context-aware (un)certainty assessment (DeepCertainty),
which is end-to-end trainable, calibratable, generalizable, scalable, and explainable. It would allow for fine-
grained uncertainty measurement and standardization, facilitate consistent and accurate diagnostic certainty
communication in CTPA reports and thus improve PE care. This study will build the foundation for future
implementation and integration of DeepCertainty into clinical workflows to prompt real-time low-certainty alerts
for improving PE diagnostic reporting quality and clarity, which will inform better treatment decisions for ED
patients with suspected PE.
PE成为心血管相关死亡的第三大原因,
每年在美国(US)发生,导致约20万人死亡和住院治疗,
超过25万名患者PE的快速和准确诊断对于确保最高的
护理质量。每年美国1.2亿急诊科(艾德)患者中有1-2%接受
CT肺血管造影(CTPA)治疗PE。转诊医生严重依赖CTPA
报告诊断或排除PE。放射学报告的清晰度是最关键的质量之一,
美国放射学会强调了在放射学报告中精确沟通的必要性。
然而,在放射学报告中有效地传达不确定性是具有挑战性的。转诊医生可能
解释放射科医生的文本表达,其传达的诊断置信度不同于预期。差距
放射科医生的预期信息和转诊医生的解释之间不能完全
通过结构化报告或标准化词典解决。CTPA报告中不必要的对冲语言
可能会进一步加剧报告的不明确性,并可能导致对患者的不适当治疗。所以我们
旨在开发一种基于深度学习的方法,用于上下文感知(un)确定性评估(deepaware),
其是端到端可训练的、可校准的、可推广的、可缩放的和可解释的。它会允许罚款-
粒度不确定性测量和标准化,促进一致和准确的诊断确定性
CTPA报告中的沟通,从而改善PE护理。本研究为今后的研究奠定了基础
将DeepMonitorty实施并集成到临床工作流程中,以提示实时低确定性警报
用于提高PE诊断报告的质量和清晰度,这将为艾德提供更好的治疗决策
疑似PE的患者。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Feifan Liu其他文献
Feifan Liu的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Feifan Liu', 18)}}的其他基金
相似海外基金
Rational design of rapidly translatable, highly antigenic and novel recombinant immunogens to address deficiencies of current snakebite treatments
合理设计可快速翻译、高抗原性和新型重组免疫原,以解决当前蛇咬伤治疗的缺陷
- 批准号:
MR/S03398X/2 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
Fellowship
Re-thinking drug nanocrystals as highly loaded vectors to address key unmet therapeutic challenges
重新思考药物纳米晶体作为高负载载体以解决关键的未满足的治疗挑战
- 批准号:
EP/Y001486/1 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
Research Grant
CAREER: FEAST (Food Ecosystems And circularity for Sustainable Transformation) framework to address Hidden Hunger
职业:FEAST(食品生态系统和可持续转型循环)框架解决隐性饥饿
- 批准号:
2338423 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
Continuing Grant
Metrology to address ion suppression in multimodal mass spectrometry imaging with application in oncology
计量学解决多模态质谱成像中的离子抑制问题及其在肿瘤学中的应用
- 批准号:
MR/X03657X/1 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
Fellowship
CRII: SHF: A Novel Address Translation Architecture for Virtualized Clouds
CRII:SHF:一种用于虚拟化云的新型地址转换架构
- 批准号:
2348066 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
Standard Grant
BIORETS: Convergence Research Experiences for Teachers in Synthetic and Systems Biology to Address Challenges in Food, Health, Energy, and Environment
BIORETS:合成和系统生物学教师的融合研究经验,以应对食品、健康、能源和环境方面的挑战
- 批准号:
2341402 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
Standard Grant
The Abundance Project: Enhancing Cultural & Green Inclusion in Social Prescribing in Southwest London to Address Ethnic Inequalities in Mental Health
丰富项目:增强文化
- 批准号:
AH/Z505481/1 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
Research Grant
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10107647 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
EU-Funded
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10106221 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
EU-Funded
Recite: Building Research by Communities to Address Inequities through Expression
背诵:社区开展研究,通过表达解决不平等问题
- 批准号:
AH/Z505341/1 - 财政年份:2024
- 资助金额:
$ 18.84万 - 项目类别:
Research Grant