{"screening_id":"IVY-CBC-20260619-CA2881","timestamp":"2026-06-19T14:15:21.351803","sex":"M","age":55,"models_run":4,"derived_ratios":{"nlr":1.75,"plr":117.8,"sii":430.0,"siri":0.84},"results":[{"cancer_type":"prostate","display_name":"Prostate Cancer","risk_tier":"Average","probability":0.3202},{"cancer_type":"lung","display_name":"Lung Cancer","risk_tier":"Average","probability":0.3705},{"cancer_type":"crc","display_name":"Colorectal Cancer","risk_tier":"Average","probability":0.3876},{"cancer_type":"multi","display_name":"Ivy Health Alert","risk_tier":"Normal","probability":0.5272}]}
curl --location --request POST 'https://zylalabs.com/api/12951/ai+cancer+risk+api/25860/cancer+risk+screen' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"sex": "M",
"age": 55,
"wbc": 6.2,
"neutrophils": 3650,
"lymphocytes": 2080,
"monocytes": 480,
"rbc": 4.50,
"hemoglobin": 14.1,
"mcv": 89.0,
"rdw": 13.3,
"mchc": 33.5,
"platelets": 245
}'
注册后,每个开发者都会被分配一个个人 API 访问密钥,这是一个唯一的字母和数字组合,用于访问我们的 API 端点。要使用 AI Cancer Risk API 进行身份验证,只需在 Authorization 标头中包含您的 bearer token。
| 标头 | 描述 |
|---|---|
授权
|
必需
应为 Bearer access_key. 订阅后,请查看上方的"您的 API 访问密钥"。
|
无长期承诺。随时升级、降级或取消。 免费试用包括最多 50 个请求。
(年度计费可节省 2 个月 🎉)
The AI Cancer Risk API enables screening for more than 20 cancer types using only data from a routine Complete Blood Count (CBC) blood test. No imaging, specialist consultation, or additional diagnostic testing is required. By analyzing standard CBC parameters, the API delivers AI-powered cancer risk assessments in under 50 milliseconds, making it ideal for health insurers, corporate wellness platforms, telehealth applications, laboratory systems, and healthcare providers seeking scalable cancer risk intelligence.
The API requires only 12 inputs: patient sex, age, and 10 standard CBC blood values. Each request generates structured risk scores, probabilities, and risk tiers across four independent cancer screening models. Depending on the patient's sex, the API evaluates either prostate cancer risk (for males) or breast cancer risk (for females), while also assessing lung cancer risk, colorectal cancer risk, and a comprehensive multi-cancer screening model known as the Ivy Health Alert.
The Ivy Health Alert is the broadest model available within the API. It detects generalized hematological patterns and blood-based abnormalities associated with a wide range of malignancies, including many cancers that currently lack routine population-wide early detection tests. The model screens for hematological cancers such as leukemia (AML, CLL, and ALL), lymphoma (Hodgkin and non-Hodgkin), multiple myeloma, myelodysplastic syndrome, polycythemia vera, and essential thrombocythemia. It also evaluates gastrointestinal cancers including colorectal, gastric, pancreatic, liver, and esophageal cancers; gynecological cancers such as ovarian, cervical, and uterine/endometrial cancers; urological cancers including prostate, bladder, and kidney cancers; as well as other major malignancies such as lung cancer, breast cancer, thyroid cancer, and sarcomas.
All risk assessments are categorized into four standardized tiers based on NHANES population percentiles. High-risk results represent the top 10% of the population and may warrant priority clinical referral. Moderate-risk results correspond to the next 15% and suggest ensuring that recommended screenings are current. Average-risk results fall within the middle 25% of the population and align with standard preventive care recommendations. Low-risk results represent the bottom 50% and generally indicate routine monitoring.
The AI Cancer Risk API is designed for organizations that already collect CBC data and want to unlock additional clinical value from existing blood tests. Health insurers and third-party administrators can integrate cancer risk indicators into annual health assessments. Corporate wellness programs can provide meaningful cancer screening insights as part of employee health benefits. Telehealth platforms and consumer health applications can enhance CBC result interpretation with AI-generated cancer risk context. Laboratory information systems and electronic health record platforms can perform silent background screening on every CBC processed, while screening clinics can offer advanced cancer risk reports alongside standard blood panel services.
With a single blood test and a single API call, the AI Cancer Risk API provides rapid, scalable screening across more than 20 cancer types, transforming routine CBC data into actionable cancer risk intelligence.
癌症风险筛查端点返回基于人工智能的前列腺、乳腺、肺癌、结直肠癌的癌症风险分数,以及多癌症警报。它根据提交的CBC参数提供结构化的风险等级(高、中、平均、低),以及每种癌症类型的概率
响应中的关键字段包括 `screening_id` `timestamp` `sex` `age` `models_run` `derived_ratios` 和 `results` `results` 字段包含每种癌症类型的详细信息,包括 `cancer_type` `display_name` `risk_tier` 和 `probability`
响应数据以JSON格式组织 包括筛查请求的摘要以及每种癌症类型的结果列表 详细说明风险等级和相关概率 这种结构便于解析和集成到应用程序中
该端点接受12个参数:`性别`、`年龄`和10个CBC血液值。用户必须提供这些参数以获得癌症风险评估。每个参数必须正确格式化以确保准确分析
通过针对NHANES人口数据训练的专有机器学习模型来保持数据的准确性 持续的模型评估和更新确保风险评估反映最新的研究和临床发现
典型的使用场景包括健康保险公司在健康检查中添加癌症风险标签 企业健康计划将癌症筛查纳入员工健康福利 以及远程医疗应用程序通过人工智能驱动的风险洞察增强CBC结果显示
用户可以通过解读风险层级和概率来利用返回的数据,以为临床决策提供信息、优先考虑患者转诊并增强预防护理策略。这种结构化格式便于与健康管理系统的轻松集成
质量检查包括输入参数的验证与已知临床数据的一致性检查以及对人工智能模型的持续性能监测这确保了可靠的输出并最小化了错误评估的风险