Abstract: Disclosed are methods of treating various disorders with anti-IL-4R? antibodies and fragments thereof.

Abstract: Disclosed are methods of treating various disorders with anti-IL-4R? antibodies and fragments thereof.

Abstract: Data processing systems for identifying new indications for a drug can include a computer-readable memory including computer-executable instructions; and at least one processor configured to execute executable logic including the computer-executable instructions and at least one machine learning model to perform one or more operations. The one or more operations can include receiving data representing medical records of a plurality of patients; selecting a set of patients; determining a plurality of patient characteristics of the set of patients; grouping, in accordance with the plurality of patient characteristics, the set of patients to generate a plurality of distinct groups, each of the distinct groups including at least one patient of the set of patients; selecting, based on one or more group selection criteria, a set of distinct groups of the plurality of distinct groups; and identifying one or more relevant patient characteristics by analyzing each distinct group of the set of distinct groups.

Abstract: Data processing systems for identifying new indications for a drug can include a computer-readable memory including computer-executable instructions; and at least one processor configured to execute executable logic including the computer-executable instructions and at least one machine learning model to perform one or more operations. The one or more operations can include receiving data representing medical records of a plurality of patients; selecting a set of patients; determining a plurality of patient characteristics of the set of patients; grouping, in accordance with the plurality of patient characteristics, the set of patients to generate a plurality of distinct groups, each of the distinct groups including at least one patient of the set of patients; selecting, based on one or more group selection criteria, a set of distinct groups of the plurality of distinct groups; and identifying one or more relevant patient characteristics by analyzing each distinct group of the set of distinct groups.

Abstract: Data processing systems for repurposing a drug can include a computer-readable memory including computer-executable instructions; and at least one processor configured to execute executable logic including the computer-executable instructions and at least one machine learning model to perform one or more operations. The one or more operations can include receiving data representing medical records of a plurality of patients; selecting a set of patients; determining a plurality of patient characteristics of the set of patients; grouping, in accordance with the plurality of patient characteristics, the set of patients to generate a plurality of distinct groups, each of the distinct groups including at least one patient of the set of patients; selecting, based on one or more group selection criteria, a set of distinct groups of the plurality of distinct groups; and identifying one or more relevant patient characteristics by analyzing each distinct group of the set of distinct groups.

Abstract: Disclosed are methods of treating various disorders with anti-IL-4R? antibodies and fragments thereof.

Abstract: Disclosed are methods of treating various disorders with anti-IL-4R? antibodies and fragments thereof.

Abstract: Disclosed are methods of treating various disorders with anti-IL-4R? antibodies and fragments thereof.

Abstract: Disclosed are methods of treating various disorders with anti-IL-4R? antibodies and fragments thereof.

Abstract: Disclosed are methods of treating various disorders with anti-IL-4R? antibodies and fragments thereof.

Abstract: Data processing systems for repurposing a drug can include a computer-readable memory including computer-executable instructions; and at least one processor configured to execute executable logic including the computer-executable instructions and at least one machine learning model to perform one or more operations. The one or more operations can include receiving data representing medical records of a plurality of patients; selecting a set of patients; determining a plurality of patient characteristics of the set of patients; grouping, in accordance with the plurality of patient characteristics, the set of patients to generate a plurality of distinct groups, each of the distinct groups including at least one patient of the set of patients; selecting, based on one or more group selection criteria, a set of distinct groups of the plurality of distinct groups; and identifying one or more relevant patient characteristics by analyzing each distinct group of the set of distinct groups.

Abstract: A shoe (200) that includes a first piece of fabric (202) having an inner perimeter (207) and an outer perimeter (205) and a first piece of conductive material, joined with the inner perimeter of the first piece of fabric, wherein an inner perimeter of the first piece of fabric surrounds the first piece of conductive material to form a conductive sole (214) and the outer perimeter of the first piece of fabric is adapted to be joined to another fabric.

Abstract: A shoe (200) that includes a first piece of fabric (202) having an inner perimeter (207) and an outer perimeter (205) and a first piece of conductive material, joined with the inner perimeter of the first piece of fabric, wherein an inner perimeter of the first piece of fabric surrounds the first piece of conductive material to form a conductive sole (214) and the outer perimeter of the first piece of fabric is adapted to be joined to another fabric.