IL310877A - Discovery platform - Google Patents
Discovery platformInfo
- Publication number
- IL310877A IL310877A IL310877A IL31087724A IL310877A IL 310877 A IL310877 A IL 310877A IL 310877 A IL310877 A IL 310877A IL 31087724 A IL31087724 A IL 31087724A IL 310877 A IL310877 A IL 310877A
- Authority
- IL
- Israel
- Prior art keywords
- model
- treatment
- embeddings
- interest
- placebo
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4848—Monitoring or testing the effects of treatment, e.g. of medication
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Biomedical Technology (AREA)
- Data Mining & Analysis (AREA)
- Pathology (AREA)
- Databases & Information Systems (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Medicinal Chemistry (AREA)
- Quality & Reliability (AREA)
- Software Systems (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Heart & Thoracic Surgery (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Veterinary Medicine (AREA)
- Artificial Intelligence (AREA)
- Mathematical Physics (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Evolutionary Computation (AREA)
- Image Analysis (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US202163233707P | 2021-08-16 | 2021-08-16 | |
| PCT/US2022/075006 WO2023023507A1 (en) | 2021-08-16 | 2022-08-16 | Discovery platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| IL310877A true IL310877A (en) | 2024-04-01 |
Family
ID=83271147
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| IL310877A IL310877A (en) | 2021-08-16 | 2022-08-16 | Discovery platform |
Country Status (8)
| Country | Link |
|---|---|
| US (4) | US12002559B2 (https=) |
| EP (1) | EP4388549A1 (https=) |
| JP (1) | JP2024534035A (https=) |
| KR (1) | KR20240068638A (https=) |
| AU (1) | AU2022328586A1 (https=) |
| CA (1) | CA3228785A1 (https=) |
| IL (1) | IL310877A (https=) |
| WO (1) | WO2023023507A1 (https=) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20240068638A (ko) | 2021-08-16 | 2024-05-17 | 인시트로, 인코포레이티드 | 발견 플랫폼 |
| WO2023092108A2 (en) | 2021-11-19 | 2023-05-25 | Insitro, Inc. | Autonomous cell imaging and modeling system |
| US12354013B2 (en) * | 2022-05-03 | 2025-07-08 | Salesforce, Inc. | Systems and methods for masked self-training of unsupervised image classification |
| CN115762796A (zh) * | 2022-09-27 | 2023-03-07 | 京东方科技集团股份有限公司 | 目标模型的获取方法、预后评估值确定方法、装置、设备及介质 |
| WO2024173610A1 (en) | 2023-02-15 | 2024-08-22 | Insitro, Inc. | Machine-learning-enabled predictive biomarker discovery and patient stratification using standard-of-care data |
| CN121175758A (zh) * | 2023-03-03 | 2025-12-19 | 豪夫迈·罗氏有限公司 | 用于生物标志物检测的系统和方法 |
| WO2025190827A1 (en) * | 2024-03-15 | 2025-09-18 | Bayer Aktiengesellschaft | Generation of a synthetic medical image |
| EP4618009A1 (en) * | 2024-03-15 | 2025-09-17 | Bayer Aktiengesellschaft | Generation of a synthetic medical image |
Family Cites Families (32)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US255924A (en) | 1882-04-04 | Corset | ||
| JP4932703B2 (ja) | 2005-03-22 | 2012-05-16 | 株式会社メディネット | 細胞培養評価システム、細胞培養評価方法および細胞培養評価プログラム |
| CN102272795B (zh) * | 2009-01-13 | 2014-09-10 | 皇家飞利浦电子股份有限公司 | 基于图像的临床试验评估 |
| US20170204359A1 (en) | 2014-12-19 | 2017-07-20 | Panasonic Corporation | Cell culture apparatus |
| US10467754B1 (en) | 2017-02-15 | 2019-11-05 | Google Llc | Phenotype analysis of cellular image data using a deep metric network |
| CN110546277B (zh) | 2017-03-01 | 2024-06-11 | 豪夫迈·罗氏有限公司 | 用于癌症的诊断和治疗方法 |
| US11107583B2 (en) * | 2018-03-20 | 2021-08-31 | Case Western Reserve University | Sequential integration of adversarial networks with handcrafted features (SANwicH): identifying sites of prognostic significance for predicting cancer recurrence |
| JP7455757B2 (ja) | 2018-04-13 | 2024-03-26 | フリーノーム・ホールディングス・インコーポレイテッド | 生体試料の多検体アッセイのための機械学習実装 |
| US10957041B2 (en) | 2018-05-14 | 2021-03-23 | Tempus Labs, Inc. | Determining biomarkers from histopathology slide images |
| US11955241B2 (en) * | 2018-06-03 | 2024-04-09 | The Regents Of The University Of California | Pathogenic biomarkers and serum extracellular vesicular biomarkers associated with vascular malformation of endothelial cells, and uses thereof |
| WO2020010163A1 (en) | 2018-07-02 | 2020-01-09 | Tempus Labs, Inc. | 3d radiomic platform for imaging biomarker development |
| EP3857564A1 (en) * | 2018-09-29 | 2021-08-04 | F. Hoffmann-La Roche AG | Multimodal machine learning based clinical predictor |
| US20200388287A1 (en) | 2018-11-13 | 2020-12-10 | CurieAI, Inc. | Intelligent health monitoring |
| JP7462632B2 (ja) | 2018-11-30 | 2024-04-05 | カリス エムピーアイ インコーポレイテッド | 次世代分子プロファイリング |
| US20220059240A1 (en) | 2018-12-31 | 2022-02-24 | Tempus Labs, Inc. | Method and process for predicting and analyzing patient cohort response, progression, and survival |
| US12118715B2 (en) | 2019-02-01 | 2024-10-15 | Owkin, Inc. | Systems and methods for image classification |
| CA3145370A1 (en) | 2019-06-25 | 2020-12-30 | Owkin Inc. | Systems and methods for mesothelioma feature detection and enhanced prognosis or response to treatment |
| WO2020261183A1 (en) | 2019-06-25 | 2020-12-30 | Owkin Inc. | Systems and methods for image preprocessing |
| US12230399B2 (en) | 2019-09-27 | 2025-02-18 | The Brigham And Women's Hospital, Inc. | Multimodal fusion for diagnosis, prognosis, and therapeutic response prediction |
| EP4070232A4 (en) | 2019-12-05 | 2024-01-31 | Tempus Labs, Inc. | SYSTEMS AND METHODS FOR HIGH-THROUGHPUT ACTIVE SCREENING |
| EP4097636A1 (en) | 2020-01-28 | 2022-12-07 | PAIGE.AI, Inc. | Systems and methods for processing electronic images for computational detection methods |
| EP3872711A1 (en) | 2020-02-28 | 2021-09-01 | Sensyne Health Group Limited | Semi-supervised machine learning method and system suitable for identification of patient subgroups in electronic healthcare records |
| WO2021205033A1 (en) | 2020-04-10 | 2021-10-14 | Koninklijke Philips N.V. | Clinically meaningful and personalized disease progression monitoring incorporating established disease staging definitions |
| US12468952B2 (en) | 2020-06-02 | 2025-11-11 | Salesforce, Inc. | Systems and methods for noise-robust contrastive learning |
| EP4211657B1 (en) | 2020-09-08 | 2024-12-11 | Insitro, Inc. | Biological image transformation using machine-learning models |
| US12271832B2 (en) | 2021-02-12 | 2025-04-08 | Tempus Ai, Inc. | Artificial intelligence engine for directed hypothesis generation and ranking |
| US12361542B2 (en) | 2021-03-03 | 2025-07-15 | Tempus Ai, Inc. | Systems and methods for deep orthogonal fusion for multimodal prognostic biomarker discovery |
| JP2023015674A (ja) | 2021-07-20 | 2023-02-01 | 株式会社エビデント | 細胞塊の内部予測方法、プログラム、及び、画像処理装置 |
| WO2023009870A1 (en) | 2021-07-29 | 2023-02-02 | Tempus Labs, Inc. | Platform for co-culture imaging to characterize in vitro efficacy of heterotypic effector cellular therapies in cancer |
| KR20240068638A (ko) | 2021-08-16 | 2024-05-17 | 인시트로, 인코포레이티드 | 발견 플랫폼 |
| WO2023092108A2 (en) | 2021-11-19 | 2023-05-25 | Insitro, Inc. | Autonomous cell imaging and modeling system |
| WO2024173610A1 (en) | 2023-02-15 | 2024-08-22 | Insitro, Inc. | Machine-learning-enabled predictive biomarker discovery and patient stratification using standard-of-care data |
-
2022
- 2022-08-16 KR KR1020247008164A patent/KR20240068638A/ko active Pending
- 2022-08-16 WO PCT/US2022/075006 patent/WO2023023507A1/en not_active Ceased
- 2022-08-16 CA CA3228785A patent/CA3228785A1/en active Pending
- 2022-08-16 AU AU2022328586A patent/AU2022328586A1/en active Pending
- 2022-08-16 JP JP2024508966A patent/JP2024534035A/ja active Pending
- 2022-08-16 EP EP22768575.7A patent/EP4388549A1/en active Pending
- 2022-08-16 IL IL310877A patent/IL310877A/en unknown
-
2023
- 2023-06-16 US US18/336,905 patent/US12002559B2/en active Active
-
2024
- 2024-04-24 US US18/645,091 patent/US12260945B2/en active Active
- 2024-04-24 US US18/645,100 patent/US12260946B2/en active Active
-
2025
- 2025-02-14 US US19/054,563 patent/US20250259723A1/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| AU2022328586A1 (en) | 2024-02-29 |
| US20240274255A1 (en) | 2024-08-15 |
| WO2023023507A1 (en) | 2023-02-23 |
| US20250259723A1 (en) | 2025-08-14 |
| US12260946B2 (en) | 2025-03-25 |
| KR20240068638A (ko) | 2024-05-17 |
| US20230360758A1 (en) | 2023-11-09 |
| US20240274254A1 (en) | 2024-08-15 |
| CA3228785A1 (en) | 2023-02-23 |
| JP2024534035A (ja) | 2024-09-18 |
| US12260945B2 (en) | 2025-03-25 |
| US12002559B2 (en) | 2024-06-04 |
| EP4388549A1 (en) | 2024-06-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| IL310877A (en) | Discovery platform | |
| IL313642A (en) | Improved histopathology classification through machine self-learning of " tissue fingerprints" | |
| Wakiya et al. | CT-based deep learning enables early postoperative recurrence prediction for intrahepatic cholangiocarcinoma | |
| Sulaimany et al. | Predicting brain network changes in Alzheimer's disease with link prediction algorithms | |
| KR20230118198A (ko) | 일반화된 질병 검출을 위해 전자 이미지들을 처리하기위한 시스템들 및 방법들 | |
| IL305267A (en) | Systems, devices, and methods for harmonization of imaging datasets including biomarkers | |
| Chicco et al. | Ten quick tips for computational analysis of medical images | |
| IL322719A (en) | Predictive biomarker discovery powered by machine learning and patient classification using standard treatment data | |
| Gunter et al. | Machine learning models of polygenic risk for enhanced prediction of Alzheimer disease endophenotypes | |
| Sharma et al. | Comparative performance analysis of binary variants of FOX optimization algorithm with half-quadratic ensemble ranking method for thyroid cancer detection | |
| IL305254A (en) | Systems, devices, and methods for providing diagnostic assessments using image analysis | |
| Zhang et al. | GAN-Augmented Naïve Bayes for identifying high-risk coronary artery disease patients using CT angiography data | |
| Cavinato et al. | Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data | |
| Shao et al. | Pixel-level classification of five histologic patterns of lung adenocarcinoma | |
| Rui et al. | Unveiling Schizophrenia: a study with generalized functional linear mixed model via the investigation of functional random effects | |
| Sekar et al. | D-TNet: a hybrid Dense Net-transformer model for robust diabetic retinopathy detection | |
| Battineni et al. | Brain imaging studies using deep neural networks in the detection of Alzheimer's Disease | |
| Rehman et al. | Opportunistic AI for enhanced cardiovascular disease risk stratification using abdominal CT scans | |
| Xing et al. | Outlook of the future landscape of artificial intelligence in medicine and new challenges | |
| Dammak et al. | Prediction of tumour mutational burden of squamous cell carcinoma using histopathology images of surgical specimens | |
| Essalah et al. | Advancing liver cancer research: a graph-based approach for ontology enrichment and link prediction | |
| Ayoubi | AI-driven diagnostics: accuracy vs. ethical considerations | |
| Cirik et al. | Exploring the Impact of CLAHE Processing on Disease Classes ‘Effusion,’‘Infiltration,’‘Atelectasis,’and ‘Mass’ in the NIH Chest XRay Dataset Using VGG16 and ResNet50 Architectures | |
| Hussain et al. | VISGAB: Virtual staining-driven GAN benchmarking for optimizing skin tissue histology | |
| Bonthala et al. | Development of a Comprehensive Lung Scan Dataset for Machine Learning-Based Lung Cancer Detection. |