AI Paving the Way for New Generation of Medical Diagnostic Devices
By LabMedica International staff writers Posted on 22 Aug 2019 |
The development of deep learning and neural networks has led to artificial intelligence (AI) gaining learning capabilities, as a result of which some new AI tools are now better than human eyes at recognizing patterns. This is paving the way for the emergence of a new generation of medical diagnostic devices that are capable of surpassing the detection skills of the best medical practitioners.
These are the latest findings of Research and Markets, (Dublin, Ireland), a global market research company.
The ability to replicate AI has made the expertise of such medical diagnostic devices accessible to a large number of patients. Additionally, AI finds numerous and diverse applications in medical diagnostics, such as image analysis for tumor detection, video detection for gait disorders and fall prediction, biochemical tests such as for diabetes or speech analysis of emotional state and psychiatric disorders. Hence, AI will significantly disrupt the traditional model of medical diagnosis.
Since 2016, companies working on the development of AI for medical imaging have made investments of more than USD 1.1 billion. In addition to big medical diagnostic systems manufacturers, the number of Intellectual Property (IP) newcomers is also important and growing. Unlike as in the case of development of new medical devices, the costs for developing AI software are moderate. As a result, the number of IP newcomers developing innovative software is likely to continue to increase sharply over the coming years.
The emergence of several new companies, coupled with the various advantages and new applications of AI for medical diagnostics, makes it crucial to understand the IP position and strategy of the different players. An analysis of the time evolution of patent publications reveals that the development of medical diagnostic systems with built-in computer-assisted detection features is not new, and the first patents related to this topic were published in the 1980s. During the 1990s, Japanese manufacturers of medical imaging systems began investing in investigations into this field to be soon followed by European companies and later by American companies. The number of patent families published each year increased progressively until 2015 and has increased rapidly since then, with more than 1,100 new patent families published in 2018. This indicates that AI in medical diagnostics is a very hot topic that is mobilizing great R&D efforts from different players.
Among the players who have filed patents related to AI in medical diagnostics, over 90 are newcomers, out of which most are startup firms currently developing their first products. These products include software solutions such as software for ultrasound imaging analysis, image resolution improvement or real-time brain monitoring, or medical devices that are capable of live analysis of biological parameters, such as blood glucose monitoring apparatus, sleep monitoring sensors and ECG. Several IP newcomers are based in the US while some are based in Israel, in Europe or in Asia. Some of these innovative companies could become one of the next healthcare unicorns, making them potential acquisition targets for big corporations.
Related Links:
Research and Markets
These are the latest findings of Research and Markets, (Dublin, Ireland), a global market research company.
The ability to replicate AI has made the expertise of such medical diagnostic devices accessible to a large number of patients. Additionally, AI finds numerous and diverse applications in medical diagnostics, such as image analysis for tumor detection, video detection for gait disorders and fall prediction, biochemical tests such as for diabetes or speech analysis of emotional state and psychiatric disorders. Hence, AI will significantly disrupt the traditional model of medical diagnosis.
Since 2016, companies working on the development of AI for medical imaging have made investments of more than USD 1.1 billion. In addition to big medical diagnostic systems manufacturers, the number of Intellectual Property (IP) newcomers is also important and growing. Unlike as in the case of development of new medical devices, the costs for developing AI software are moderate. As a result, the number of IP newcomers developing innovative software is likely to continue to increase sharply over the coming years.
The emergence of several new companies, coupled with the various advantages and new applications of AI for medical diagnostics, makes it crucial to understand the IP position and strategy of the different players. An analysis of the time evolution of patent publications reveals that the development of medical diagnostic systems with built-in computer-assisted detection features is not new, and the first patents related to this topic were published in the 1980s. During the 1990s, Japanese manufacturers of medical imaging systems began investing in investigations into this field to be soon followed by European companies and later by American companies. The number of patent families published each year increased progressively until 2015 and has increased rapidly since then, with more than 1,100 new patent families published in 2018. This indicates that AI in medical diagnostics is a very hot topic that is mobilizing great R&D efforts from different players.
Among the players who have filed patents related to AI in medical diagnostics, over 90 are newcomers, out of which most are startup firms currently developing their first products. These products include software solutions such as software for ultrasound imaging analysis, image resolution improvement or real-time brain monitoring, or medical devices that are capable of live analysis of biological parameters, such as blood glucose monitoring apparatus, sleep monitoring sensors and ECG. Several IP newcomers are based in the US while some are based in Israel, in Europe or in Asia. Some of these innovative companies could become one of the next healthcare unicorns, making them potential acquisition targets for big corporations.
Related Links:
Research and Markets
Latest Industry News
- Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions
- Grifols and Tecan’s IBL Collaborate on Advanced Biomarker Panels
- New Collaboration to Advance Microbial Identification for Infectious Disease Diagnostics
- Tecan Acquires ELISA Immunoassay Assets from Revvity's Cisbio Bioassays
- Leica Biosystems and Bio-Techne Expand Spatial Multiomic Collaboration
- Philips and Ibex Expand Partnership to Enhance AI-Enabled Pathology Workflows
- Grifols and Inpeco Partner to Deliver Transfusion Medicine ‘Lab of The Future’
- Research Collaboration to Advance AI-Enhanced, Real-Time Optical Imaging in Lung Cancer Biopsy
- CACLP 2025 Unites Global Innovators in IVD Industry
- Bio-Rad to Acquire Digital PCR Developer Stilla Technologies
- ABL Signs Know-How License and Transfer Agreement for Siemens’ Fast Track Diagnostics PCR Portfolio
- Becton Dickinson to Spin Out Biosciences and Diagnostic Solutions Business
- New Partnership Revolutionizes Analyses of Biological Samples
- Medlab Middle East Looks to The Future of Laboratories
- Medix Biochemica Acquires German Immunoassay Solutions Developer Candor Bioscience
- bioMérieux Acquires Norwegian Immunoassay Start-Up SpinChip Diagnostics
Channels
Clinical Chemistry
view channel
Mass Spectrometry-Based Monitoring Technique to Predict and Identify Early Myeloma Relapse
Myeloma, a type of cancer that affects the bone marrow, is currently incurable, though many patients can live for over 10 years after diagnosis. However, around 1 in 5 individuals with myeloma have a high-risk... Read more
‘Brilliantly Luminous’ Nanoscale Chemical Tool to Improve Disease Detection
Thousands of commercially available glowing molecules known as fluorophores are commonly used in medical imaging, disease detection, biomarker tagging, and chemical analysis. They are also integral in... Read more
Low-Cost Portable Screening Test to Transform Kidney Disease Detection
Millions of individuals suffer from kidney disease, which often remains undiagnosed until it has reached a critical stage. This silent epidemic not only diminishes the quality of life for those affected... Read more
New Method Uses Pulsed Infrared Light to Find Cancer's 'Fingerprints' In Blood Plasma
Cancer diagnoses have traditionally relied on invasive or time-consuming procedures like tissue biopsies. Now, new research published in ACS Central Science introduces a method that utilizes pulsed infrared... Read moreMolecular Diagnostics
view channel
New Genetic Tool Analyzes Umbilical Cord Blood to Predict Future Disease
Children are experiencing metabolic problems at increasingly younger ages, placing them at higher risk for serious health issues later in life. There is a growing need to identify this risk from birth... Read more
Spinal Fluid Biomarker for Parkinson’s Disease Offers Early and Accurate Diagnosis
Parkinson’s disease is a neurodegenerative condition typically diagnosed at an advanced stage based on clinical symptoms, primarily motor disorders. However, by this time, the brain has already undergone... Read moreHematology
view channel
New Scoring System Predicts Risk of Developing Cancer from Common Blood Disorder
Clonal cytopenia of undetermined significance (CCUS) is a blood disorder commonly found in older adults, characterized by mutations in blood cells and a low blood count, but without any obvious cause or... Read more
Non-Invasive Prenatal Test for Fetal RhD Status Demonstrates 100% Accuracy
In the United States, approximately 15% of pregnant individuals are RhD-negative. However, in about 40% of these cases, the fetus is also RhD-negative, making the administration of RhoGAM unnecessary.... Read moreImmunology
view channel
Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer
Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more
Machine Learning-Enabled Blood Test Predicts Immunotherapy Response in Lymphoma Patients
Chimeric antigen receptor (CAR) T-cell therapy has emerged as one of the most promising recent developments in the treatment of blood cancers. However, over half of non-Hodgkin lymphoma (NHL) patients... Read moreMicrobiology
view channel
New Test Diagnoses Bacterial Meningitis Quickly and Accurately
Bacterial meningitis is a potentially fatal condition, with one in six patients dying and half of the survivors experiencing lasting symptoms. Therefore, rapid diagnosis and treatment are critical.... Read more
Handheld Device Delivers Low-Cost TB Results in Less Than One Hour
Tuberculosis (TB) remains the deadliest infectious disease globally, affecting an estimated 10 million people annually. In 2021, about 4.2 million TB cases went undiagnosed or unreported, mainly due to... Read more
New AI-Based Method Improves Diagnosis of Drug-Resistant Infections
Drug-resistant infections, particularly those caused by deadly bacteria like tuberculosis and staphylococcus, are rapidly emerging as a global health emergency. These infections are more difficult to treat,... Read more
Breakthrough Diagnostic Technology Identifies Bacterial Infections with Almost 100% Accuracy within Three Hours
Rapid and precise identification of pathogenic microbes in patient samples is essential for the effective treatment of acute infectious diseases, such as sepsis. The fluorescence in situ hybridization... Read morePathology
view channel
AI-Based Model Predicts Kidney Cancer Therapy Response
Each year, nearly 435,000 individuals are diagnosed with clear cell renal cell carcinoma (ccRCC), making it the most prevalent subtype of kidney cancer. When the disease spreads, anti-angiogenic therapies... Read more
Sensitive and Specific DUB Enzyme Assay Kits Require Minimal Setup Without Substrate Preparation
Ubiquitination and deubiquitination are two important physiological processes in the ubiquitin-proteasome system, responsible for protein degradation in cells. Deubiquitinating (DUB) enzymes contain around... Read moreTechnology
view channel
Disposable Microchip Technology Could Selectively Detect HIV in Whole Blood Samples
As of the end of 2023, approximately 40 million people globally were living with HIV, and around 630,000 individuals died from AIDS-related illnesses that same year. Despite a substantial decline in deaths... Read more
Pain-On-A-Chip Microfluidic Device Determines Types of Chronic Pain from Blood Samples
Chronic pain is a widespread condition that remains difficult to manage, and existing clinical methods for its treatment rely largely on self-reporting, which can be subjective and especially problematic... Read more