AI-AlgoStore
Choose among the best curated Algorithms for your real life projects
Explainable AI Biotech/Pharma
Augment with an
AI-Analyst
Rare Diseases
When it comes to drugs and medical treatments there is no "one-size-fits-all." Patients vary greatly in their needs and responses. A treatment that is life-saving for one person might be ineffective or even harmful to another. This realization has led to the revolution of personalized medicine and drug design. It is helpful here that there is a certain degree of commonality among people. Much can be learned from partitioning the overall population of patients into subpopulations that share certain common features and attributes. However, identifying well-defined subpopulations remains to be a challenging endeavor. While there is nowadays no shortage in data that can be used to minutely characterize individual patients and the symptoms they exhibit, these detailed characterizations lead to vast and unwieldy feature spaces where patient subpopulations are rarely homogeneous and often difficult to separate. .......Read more in use case
Explainable AI Biotech/Pharma
Augment with an
AI-Analyst
Treatment prognosis
When it comes to drugs and medical treatments there is no "one-size-fits-all." Patients vary greatly in their needs and responses. A treatment that is life-saving for one person might be ineffective or even harmful to another. This realization has led to the revolution of personalized medicine and drug design. It is helpful here that there is a certain degree of commonality among people. Much can be learned from partitioning the overall population of patients into subpopulations that share certain common features and attributes. However, identifying well-defined subpopulations remains to be a challenging endeavor. While there is nowadays no shortage in data that can be used to minutely characterize individual patients and the symptoms they exhibit, these detailed characterizations lead to vast and unwieldy feature spaces where patient subpopulations are rarely homogeneous and often difficult to separate. .......Read more in use case
Explainable AI Biotech/Pharma
Augment with an
AI-Analyst
Drug testing and validation
When it comes to drugs and medical treatments there is no "one-size-fits-all." Patients vary greatly in their needs and responses. A treatment that is life-saving for one person might be ineffective or even harmful to another. This realization has led to the revolution of personalized medicine and drug design. It is helpful here that there is a certain degree of commonality among people. Much can be learned from partitioning the overall population of patients into subpopulations that share certain common features and attributes. However, identifying well-defined subpopulations remains to be a challenging endeavor. While there is nowadays no shortage in data that can be used to minutely characterize individual patients and the symptoms they exhibit, these detailed characterizations lead to vast and unwieldy feature spaces where patient subpopulations are rarely homogeneous and often difficult to separate. .......Read more in use case
Explainable AI Biotech/Pharma
Augment with an
AI-Analyst
Drug re-purposing
When it comes to drugs and medical treatments there is no "one-size-fits-all." Patients vary greatly in their needs and responses. A treatment that is life-saving for one person might be ineffective or even harmful to another. This realization has led to the revolution of personalized medicine and drug design. It is helpful here that there is a certain degree of commonality among people. Much can be learned from partitioning the overall population of patients into subpopulations that share certain common features and attributes. However, identifying well-defined subpopulations remains to be a challenging endeavor. While there is nowadays no shortage in data that can be used to minutely characterize individual patients and the symptoms they exhibit, these detailed characterizations lead to vast and unwieldy feature spaces where patient subpopulations are rarely homogeneous and often difficult to separate. .......Read more in use case
Explainable AI FinTech
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AI-Analyst
Stock market prediction
The ubiquitous collection and availability of big data has brought tremendous opportunities for the financial sector and also for many business sectors. It allows highly personalized assessments of risks and prospects which can then be turned into substantial profits for companies, large and small.
However, raw financial data are typically rather noisy at low veracity, and to overlook or misinterpret even small nuances and trends in these data can be extremely costly. There also is a high amount of engineering to design sensitive predictive metrics from these data, which ups the game even further.
The goal of financial analytics is prediction and better even, prescription – recommendations on actions that mitigate risk and maximize profits. Both must be grounded in exquisite, ideally superior, knowledge of the domain at hand. Formalizing this knowledge from data is the job of descriptive analytics......Read more in use case
Explainable AI FinTech
Augment with an
AI-Analyst
Fraud detection and prevention
The ubiquitous collection and availability of big data has brought tremendous opportunities for the financial sector and also for many business sectors. It allows highly personalized assessments of risks and prospects which can then be turned into substantial profits for companies, large and small.
However, raw financial data are typically rather noisy at low veracity, and to overlook or misinterpret even small nuances and trends in these data can be extremely costly. There also is a high amount of engineering to design sensitive predictive metrics from these data, which ups the game even further.
The goal of financial analytics is prediction and better even, prescription – recommendations on actions that mitigate risk and maximize profits. Both must be grounded in exquisite, ideally superior, knowledge of the domain at hand. Formalizing this knowledge from data is the job of descriptive analytics......Read more in use case
Explainable AI FinTech
Augment with an
AI-Analyst
Credit scoring
The ubiquitous collection and availability of big data has brought tremendous opportunities for the financial sector and also for many business sectors. It allows highly personalized assessments of risks and prospects which can then be turned into substantial profits for companies, large and small.
However, raw financial data are typically rather noisy at low veracity, and to overlook or misinterpret even small nuances and trends in these data can be extremely costly. There also is a high amount of engineering to design sensitive predictive metrics from these data, which ups the game even further.
The goal of financial analytics is prediction and better even, prescription – recommendations on actions that mitigate risk and maximize profits. Both must be grounded in exquisite, ideally superior, knowledge of the domain at hand. Formalizing this knowledge from data is the job of descriptive analytics......Read more in use case
Explainable AI FinTech
Augment with an
AI-Analyst
Risk management
The ubiquitous collection and availability of big data has brought tremendous opportunities for the financial sector and also for many business sectors. It allows highly personalized assessments of risks and prospects which can then be turned into substantial profits for companies, large and small.
However, raw financial data are typically rather noisy at low veracity, and to overlook or misinterpret even small nuances and trends in these data can be extremely costly. There also is a high amount of engineering to design sensitive predictive metrics from these data, which ups the game even further.
The goal of financial analytics is prediction and better even, prescription – recommendations on actions that mitigate risk and maximize profits. Both must be grounded in exquisite, ideally superior, knowledge of the domain at hand. Formalizing this knowledge from data is the job of descriptive analytics......Read more in use case
Explainable AI FinTech
Augment with an
AI-Analyst
Personalized marketing
The ubiquitous collection and availability of big data has brought tremendous opportunities for the financial sector and also for many business sectors. It allows highly personalized assessments of risks and prospects which can then be turned into substantial profits for companies, large and small.
However, raw financial data are typically rather noisy at low veracity, and to overlook or misinterpret even small nuances and trends in these data can be extremely costly. There also is a high amount of engineering to design sensitive predictive metrics from these data, which ups the game even further.
The goal of financial analytics is prediction and better even, prescription – recommendations on actions that mitigate risk and maximize profits. Both must be grounded in exquisite, ideally superior, knowledge of the domain at hand. Formalizing this knowledge from data is the job of descriptive analytics......Read more in use case