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Artificial intelligence (AI) is a simulation of the process of human intelligence through computers.
AI has cemented its status as a powerful technology with the ability to propel a paradigm shift in healthcare and medicine of the 21st century and the future. The insights and values gained from AI and its subset, machine learning, are essential for predicting health outcomes and improving decision-making in healthcare and medicine.
AI can offer revolutionary insights into medicine, through data from genetics, proteomics and other life sciences that advance the process of drug discovery and development. Discovering drugs is a crucial first step in the biopharmaceutical value chain. Drug discovery is a long, expensive and often unsuccessful process. The biopharmaceutical industry makes efforts to employ AI to improve drug discovery, reduce research and development costs, reduce the time and cost of early drug discovery, and support predicting potential risks/side effects in late clinical trials that can be useful in avoiding traumatic events in clinical trials.
The rapid growth in life sciences and machine learning algorithms has led to enormous statistical access to the growth of AI-based start-ups focused on drug innovation in recent years. The growing need to curb drug discovery costs and reduce time involved in the drug development process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of this market.
However, shortage of AI workforce and ambiguous regulatory guidelines for medical software and lack of data sets in this field are some of the factors expected to restrain the growth of this market in the coming years.
AI has cemented its status as a powerful technology with the ability to propel a paradigm shift in healthcare and medicine of the 21st century and the future. The insights and values gained from AI and its subset, machine learning, are essential for predicting health outcomes and improving decision-making in healthcare and medicine.
AI can offer revolutionary insights into medicine, through data from genetics, proteomics and other life sciences that advance the process of drug discovery and development. Discovering drugs is a crucial first step in the biopharmaceutical value chain. Drug discovery is a long, expensive and often unsuccessful process. The biopharmaceutical industry makes efforts to employ AI to improve drug discovery, reduce research and development costs, reduce the time and cost of early drug discovery, and support predicting potential risks/side effects in late clinical trials that can be useful in avoiding traumatic events in clinical trials.
The rapid growth in life sciences and machine learning algorithms has led to enormous statistical access to the growth of AI-based start-ups focused on drug innovation in recent years. The growing need to curb drug discovery costs and reduce time involved in the drug development process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of this market.
However, shortage of AI workforce and ambiguous regulatory guidelines for medical software and lack of data sets in this field are some of the factors expected to restrain the growth of this market in the coming years.
Artificial intelligence (AI) is a simulation of the process of human intelligence through computers.
AI has cemented its status as a powerful technology with the ability to propel a paradigm shift in healthcare and medicine of the 21st century and the future. The insights and values gained from AI and its subset, machine learning, are essential for predicting health outcomes and improving decision-making in healthcare and medicine.
AI can offer revolutionary insights into medicine, through data from genetics, proteomics and other life sciences that advance the process of drug discovery and development. Discovering drugs is a crucial first step in the biopharmaceutical value chain. Drug discovery is a long, expensive and often unsuccessful process. The biopharmaceutical industry makes efforts to employ AI to improve drug discovery, reduce research and development costs, reduce the time and cost of early drug discovery, and support predicting potential risks/side effects in late clinical trials that can be useful in avoiding traumatic events in clinical trials.
The rapid growth in life sciences and machine learning algorithms has led to enormous statistical access to the growth of AI-based start-ups focused on drug innovation in recent years. The growing need to curb drug discovery costs and reduce time involved in the drug development process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of this market.
However, shortage of AI workforce and ambiguous regulatory guidelines for medical software and lack of data sets in this field are some of the factors expected to restrain the growth of this market in the coming years.
AI has cemented its status as a powerful technology with the ability to propel a paradigm shift in healthcare and medicine of the 21st century and the future. The insights and values gained from AI and its subset, machine learning, are essential for predicting health outcomes and improving decision-making in healthcare and medicine.
AI can offer revolutionary insights into medicine, through data from genetics, proteomics and other life sciences that advance the process of drug discovery and development. Discovering drugs is a crucial first step in the biopharmaceutical value chain. Drug discovery is a long, expensive and often unsuccessful process. The biopharmaceutical industry makes efforts to employ AI to improve drug discovery, reduce research and development costs, reduce the time and cost of early drug discovery, and support predicting potential risks/side effects in late clinical trials that can be useful in avoiding traumatic events in clinical trials.
The rapid growth in life sciences and machine learning algorithms has led to enormous statistical access to the growth of AI-based start-ups focused on drug innovation in recent years. The growing need to curb drug discovery costs and reduce time involved in the drug development process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of this market.
However, shortage of AI workforce and ambiguous regulatory guidelines for medical software and lack of data sets in this field are some of the factors expected to restrain the growth of this market in the coming years.
Über den Autor
Dr Mbuso Mabuza is a highly motivated life-long learner and multi-skilled global health professional. Dr Mabuza's mission is to improve health outcomes and to expand quality healthcare experiences amongst all groups of people and influence change and innovation.
Details
Erscheinungsjahr: | 2023 |
---|---|
Fachbereich: | Allgemeine Lexika |
Genre: | Importe, Medizin |
Rubrik: | Wissenschaften |
Medium: | Taschenbuch |
ISBN-13: | 9798223379478 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Mabuza, Mbuso |
Hersteller: | Lekwandza Media |
Verantwortliche Person für die EU: | Books on Demand GmbH, In de Tarpen 42 In de Tarpen 42, D-22848 Norderstedt, info@bod.de |
Maße: | 216 x 140 x 5 mm |
Von/Mit: | Mbuso Mabuza |
Erscheinungsdatum: | 31.05.2023 |
Gewicht: | 0,102 kg |
Über den Autor
Dr Mbuso Mabuza is a highly motivated life-long learner and multi-skilled global health professional. Dr Mabuza's mission is to improve health outcomes and to expand quality healthcare experiences amongst all groups of people and influence change and innovation.
Details
Erscheinungsjahr: | 2023 |
---|---|
Fachbereich: | Allgemeine Lexika |
Genre: | Importe, Medizin |
Rubrik: | Wissenschaften |
Medium: | Taschenbuch |
ISBN-13: | 9798223379478 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Mabuza, Mbuso |
Hersteller: | Lekwandza Media |
Verantwortliche Person für die EU: | Books on Demand GmbH, In de Tarpen 42 In de Tarpen 42, D-22848 Norderstedt, info@bod.de |
Maße: | 216 x 140 x 5 mm |
Von/Mit: | Mbuso Mabuza |
Erscheinungsdatum: | 31.05.2023 |
Gewicht: | 0,102 kg |
Sicherheitshinweis