The precision diagnostics market in Asia Pacific is expected to grow from US$ 15,157.61 million in 2022 to US$ 33,007.52 million by 2028. It is estimated to grow at a CAGR of 13.8% from 2022 to 2028.
The advancement in artificial intelligence (AI) is increasing. Healthcare is expected to lead the way in AI investments between 2018 and 2022, with the Asia Pacific region well-positioned to grow due to its fertile digital ecosystem, as per Industry analysts. According to the recently released Philips Future Health Index, healthcare professionals in Singapore are leaders in using AI, with 55% using AI in their daily practice compared to an average of 46% across the 15 countries surveyed. Diagnosis of complex diseases such as cancer can be time-consuming and labor-intensive because many factors are to be considered, such as disease type, physical exams, genomic and molecular data analysis, and the patient’s medical history. Intelligently aggregating all this information is the hallmark of precision diagnosis.
As per a study by International Data Corporation (IDC), the amount of data in healthcare is growing by an estimated 48% every year, leaving less time for physicians to study it. In addition, the rising disease burden in the aging population would increase the data mount. In a country, such as Singapore, up to eight in ten doctors report feeling burnt out as they struggle to keep up with the rising workload. By automating the mundane and speeding up workflows, AI can help alleviate overburdened physicians.
The ability of AI to shift through large amounts of data has the potential to make medical examinations more precise, reliable, and efficient. For instance, in CT-based lung cancer screening, Philips researchers have demonstrated that a deep learning algorithm can be helpful to radiologists as a decision support tool. Similarly, in digital pathology, algorithms can help point to regions of interest in tissue samples that demand further inspection by the pathologist. Targeted treatments that enable an individual to get better can be understood by unraveling the molecular mechanisms that give rise to an individual’s disease. Moreover, in healthcare, machine learning (ML) can be beneficial in many areas, including biomedical data management, automation of diagnoses, and biomarker discovery. Biomarker discovery can be used to build better biomarkers to predict a patient’s response to therapy. The big data from a biological system, such as the human body, needs to be understood to do so.
The current method of applying MI to biomarker discovery is making feature selections across multiple levels of omics data that predict outcomes between different cohorts. The power of MI and Ribonucleic acid (RNA) to build Health Expression Models can also help capture complex biology and enable quantification in heterogeneous tissue samples. Thus, using MI to make precision diagnostics will change the future of precision medicine, allowing the right patient to receive proper treatment at the right time.
Machine learning and artificial intelligence techniques are starting to provide doctors with new diagnostic insights. A French start-up, VitaDx, uses fluorescent imaging and MI to improve the early diagnosis of bladder cancer by analyzing the shape, physiology, and metabolism of potentially cancerous cells. The technology can also be applied later for the early diagnosis of cancers of the lungs, stomach, and thyroid. Therefore, the advantages offered by AI and MI are expected to create numerous future trends for the precision diagnostics market .
The advancement in artificial intelligence (AI) is increasing. Healthcare is expected to lead the way in AI investments between 2018 and 2022, with the Asia Pacific region well-positioned to grow due to its fertile digital ecosystem, as per Industry analysts. According to the recently released Philips Future Health Index, healthcare professionals in Singapore are leaders in using AI, with 55% using AI in their daily practice compared to an average of 46% across the 15 countries surveyed. Diagnosis of complex diseases such as cancer can be time-consuming and labor-intensive because many factors are to be considered, such as disease type, physical exams, genomic and molecular data analysis, and the patient’s medical history. Intelligently aggregating all this information is the hallmark of precision diagnosis.
As per a study by International Data Corporation (IDC), the amount of data in healthcare is growing by an estimated 48% every year, leaving less time for physicians to study it. In addition, the rising disease burden in the aging population would increase the data mount. In a country, such as Singapore, up to eight in ten doctors report feeling burnt out as they struggle to keep up with the rising workload. By automating the mundane and speeding up workflows, AI can help alleviate overburdened physicians.
The ability of AI to shift through large amounts of data has the potential to make medical examinations more precise, reliable, and efficient. For instance, in CT-based lung cancer screening, Philips researchers have demonstrated that a deep learning algorithm can be helpful to radiologists as a decision support tool. Similarly, in digital pathology, algorithms can help point to regions of interest in tissue samples that demand further inspection by the pathologist. Targeted treatments that enable an individual to get better can be understood by unraveling the molecular mechanisms that give rise to an individual’s disease. Moreover, in healthcare, machine learning (ML) can be beneficial in many areas, including biomedical data management, automation of diagnoses, and biomarker discovery. Biomarker discovery can be used to build better biomarkers to predict a patient’s response to therapy. The big data from a biological system, such as the human body, needs to be understood to do so.
The current method of applying MI to biomarker discovery is making feature selections across multiple levels of omics data that predict outcomes between different cohorts. The power of MI and Ribonucleic acid (RNA) to build Health Expression Models can also help capture complex biology and enable quantification in heterogeneous tissue samples. Thus, using MI to make precision diagnostics will change the future of precision medicine, allowing the right patient to receive proper treatment at the right time.
Machine learning and artificial intelligence techniques are starting to provide doctors with new diagnostic insights. A French start-up, VitaDx, uses fluorescent imaging and MI to improve the early diagnosis of bladder cancer by analyzing the shape, physiology, and metabolism of potentially cancerous cells. The technology can also be applied later for the early diagnosis of cancers of the lungs, stomach, and thyroid. Therefore, the advantages offered by AI and MI are expected to create numerous future trends for the precision diagnostics market .
Asia Pacific Precision Diagnostics Market Segmentation
The Asia Pacific precision diagnostics market is segmented by type, application, end user, and country.- Based on type, the market is segmented into genetic tests, esoteric tests, and others. The genetic tests segment dominated the market in 2022.
- Based on application, the market is fragmented into oncology, cardiology, immunology, respiratory diseases, and others. The oncology segment dominated the market in 2022.
- Based on end user, the market is segmented into hospitals, clinical laboratories, home care, and others. The clinical laboratories segment dominated the market in 2022.
- Based on country, the market is segmented into China, Japan, India, South Korea, Australia, and the rest of Asia Pacific. Further, China dominated the market in 2022.
Table of Contents
1. Introduction
3. Research Methodology
4. APAC Precision Diagnostics Market - Market Landscape
5. APAC Precision Diagnostics Market - Key Market Dynamics
6. Precision Diagnostics Market- APAC Analysis
7. APAC Precision Diagnostics Market- by Type
8. APAC Precision Diagnostics Market- by Application
9. APAC Precision Diagnostics Market- by End User
10. APAC Precision Diagnostics Market- by Country
11. APAC Precision Diagnostics Market -Industry Landscape
12. Company Profiles
13. Appendix
Companies Mentioned
- Abbott
- Bayer AG
- Koninklijke Philips N.V.
- Novartis AG
- QIAGEN
- Quest Diagnostics Incorporated
- Sanofi
- Siemens Healthineers AG
- Swiss Precision Diagnostics GmbH
Table Information
Report Attribute | Details |
---|---|
No. of Pages | 142 |
Published | September 2022 |
Forecast Period | 2022 - 2028 |
Estimated Market Value ( USD | $ 15157.61 Million |
Forecasted Market Value ( USD | $ 33007.52 Million |
Compound Annual Growth Rate | 13.8% |
Regions Covered | Asia Pacific |
No. of Companies Mentioned | 9 |